Solana Surges: Unraveling the Ascendancy of the High-Speed Blockchain 

 Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the evolution of high performance blockchain powered cryptocurrency, Solana.

Historical context and background

Solana, a relatively new entrant in the cryptocurrency arena, emerged against the backdrop of an increasingly crowded and competitive landscape in the digital currency space. Founded in 2020 by Anatoly Yakovenko, a former engineer at Qualcomm, Solana sought to address some of the inherent scalability and speed limitations plaguing earlier blockchain platforms like Ethereum. The platform is named after the Solana Beach in California, where Yakovenko often surfed, symbolizing the project’s ambition to ride the waves of innovation and technological advancement.

Unlike many other cryptocurrencies that primarily rely on Proof of Work (PoW) or Proof of Stake (PoS) consensus mechanisms, Solana introduced a novel consensus mechanism known as Proof of History (PoH). This mechanism aims to optimize transaction processing speed by organizing transactions into a series of chronological events, enabling parallel transaction processing, and significantly enhancing scalability. Solana’s emphasis on scalability and throughput has positioned it as a promising platform for decentralized applications (dApps) and decentralized finance (DeFi) projects seeking high-performance blockchain infrastructure. Its innovative approach has garnered attention and support from investors and developers alike, propelling Solana into the spotlight as one of the leading contenders in the cryptocurrency space.

Solana Logo

Source: Google.

Figure 1. Key Dates in Solana History.

Source: Yahoo! Finance.

Key features

    Scalability

    Solana is designed to be highly scalable, capable of processing thousands of transactions per second. Its unique consensus mechanism, Proof of History (PoH), combined with a network of nodes running parallel processing, enables Solana to handle a high throughput of transactions efficiently.

    Fast Transaction Speeds

    With its focus on scalability, Solana boasts incredibly fast transaction speeds. Transactions can be confirmed in milliseconds, making it suitable for applications requiring rapid transaction processing, such as decentralized finance (DeFi) platforms and high-frequency trading.

    Low Transaction Costs

    Solana aims to keep transaction costs low, even during periods of high network activity. Its efficient use of resources and high throughput allow for cost-effective transactions, making it accessible to users and developers alike.

    Proof of History (PoH)

    Solana’s unique consensus mechanism, PoH, serves as a historical record for the ordering and time-stamping of transactions. By leveraging PoH, Solana achieves high throughput without sacrificing decentralization or security.

    Support for Smart Contracts

    Solana is compatible with smart contracts, allowing developers to build decentralized applications (dApps) and execute programmable transactions on the blockchain. It supports smart contract languages like Rust and Solidity, enabling a wide range of developers to build on the platform.

    Ecosystem and Development Tools

    Solana boasts a growing ecosystem of projects and development tools to support developers in building decentralized applications. Its developer-friendly environment includes tools such as Solana Studio, a web-based IDE for building and deploying smart contracts, and libraries for interacting with the Solana blockchain.

    Interoperability

    Solana is designed to be interoperable with other blockchains and protocols, facilitating seamless communication and asset transfer between different networks. This interoperability opens up possibilities for cross-chain decentralized applications and enhances the overall utility of the Solana ecosystem.

Use cases

    Non-Fungible Tokens (NFTs)

    Solana provides an efficient infrastructure for minting, trading, and storing NFTs. Artists, creators, and collectors are utilizing Solana-based marketplaces like Solanart to buy and sell digital collectibles, artwork, and virtual assets. Solana’s high throughput enables seamless NFT transactions, while its low fees make it appealing for creators seeking an alternative to Ethereum’s congested network.

    Gaming and Virtual Worlds

    Solana’s high-performance blockchain is well-suited for gaming applications and virtual worlds that require fast transaction processing and scalability. Game developers are leveraging Solana’s infrastructure to create blockchain-based games, in-game assets, and decentralized gaming platforms. Projects like Star Atlas, a space-themed massively multiplayer online game (MMO) built on Solana, demonstrate the platform’s potential to disrupt the gaming industry.

    Decentralized Autonomous Organizations (DAOs)

    Solana provides a robust framework for building decentralized autonomous organizations (DAOs) that enable community governance and decision-making. DAOs on Solana leverage smart contracts to automate voting mechanisms, distribute governance tokens, and execute proposals transparently and efficiently. These DAOs empower communities to collectively manage and govern decentralized protocols, platforms, and resources.

    Tokenization of Real-World Assets

    Solana facilitates the tokenization of real-world assets such as real estate, stocks, and commodities, enabling fractional ownership and increased liquidity. Projects are exploring Solana’s blockchain to tokenize and trade various asset classes, unlocking new investment opportunities and reducing barriers to entry for traditional markets.

Technology and underlying blockchain

At the core of Solana’s architecture is the Proof of History (PoH) consensus mechanism, which orders transactions before they are processed into blocks. This deterministic sequencing allows for parallel transaction processing and enhances overall network efficiency. Additionally, Solana utilizes a Byzantine Fault Tolerance (BFT) consensus algorithm called Tower BFT, which further ensures network security and integrity.

Solana’s blockchain implements a novel data structure known as the “Solana Architecture,” which includes a combination of a single global state, a high-speed networking stack, and a high-performance virtual machine (VM). This architecture enables Solana to achieve impressive transaction throughput, with the capability to process thousands of transactions per second (TPS) and sub-second transaction finality. Furthermore, Solana leverages a unique mechanism called “Turbine” to optimize block propagation and reduce network latency, enhancing the overall scalability and performance of the platform.

The Solana ecosystem also features a built-in decentralized exchange (DEX), supporting seamless token swaps and liquidity provision directly on-chain. Smart contracts on Solana are executed using a high-performance VM called Sealevel, which is designed to efficiently process complex computations while maintaining low transaction costs. Overall, Solana’s technology stack, comprising innovative consensus mechanisms, advanced data structures, and optimized networking protocols, positions it as a leading blockchain platform capable of supporting a wide range of decentralized applications (dApps) and use cases at scale.

Supply of coins

Solana (SOL) operates on a fixed supply model, with a maximum supply of 489,026,837 SOL tokens. Unlike traditional fiat currencies, Solana’s tokenomics are governed by the principles of cryptocurrency protocols. The initial distribution of SOL tokens occurred through a combination of token sales, strategic partnerships, ecosystem incentives, and network validators’ rewards. Notably, Solana employs a deflationary economic model, wherein a portion of transaction fees is burned, reducing the overall token supply over time. This deflationary mechanism is designed to counterbalance any potential inflationary pressures as the network expands, ensuring the long-term sustainability and scarcity of SOL tokens. Additionally, SOL tokens are used to facilitate various functions within the Solana ecosystem, including transaction fees, staking rewards, governance participation, and decentralized application interactions. As Solana continues to grow and gain adoption, the controlled and predictable token supply dynamics play a crucial role in maintaining the network’s integrity and value proposition.

Historical data for Solana

How to get the data?

The Solana (SOL) is a popular cryptocurrency on the market, and historical data for the Solana such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for Solana on Yahoo! Finance (the Yahoo! code for Solana is SOL-USD).

Figure 2. Solana data

Source: Yahoo! Finance.

Historical data for the Solana market prices

The historical data for Solana market prices demonstrates a dynamic evolution marked by significant fluctuations and notable trends since its inception. Initially, SOL experienced modest trading activity and price levels, but as Solana gained recognition for its innovative blockchain architecture and scalability features, its market value began to ascend. Early adopters and investors drove demand for SOL tokens, leading to periods of rapid appreciation interspersed with corrections and consolidation phases. Milestones such as protocol upgrades, partnerships, and successful dApp launches often coincided with significant price movements. Moreover, broader market trends and sentiment towards cryptocurrencies influenced SOL’s price dynamics, contributing to both bullish and bearish cycles over time. Overall, SOL’s price trajectory reflects Solana’s journey from its early stages to becoming a prominent player in the blockchain space, highlighting its potential to revolutionize decentralized applications and digital finance despite the inherent volatility of the cryptocurrency market.

Figure 3 below represents the evolution of the price of Solana (SOL) in US dollar over the period April 2020 – December 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 3. Evolution of the Solana (SOL) price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Solana (SOL).

Download R file

The R program that you can download above allows you to download the data for the Solana (SOL) from the Yahoo! Finance website. The database starts on April, 2020.

Table 1 below represents the top of the data file for the Solana (SOL) downloaded from the Yahoo! Finance website with the R program.

Table 1. Top of the data file for the Solana (SOL)

Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Download the Python code for USD Coin data

Python script to download Solana (SOL) historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for Solana Coin

SOL_ticker = “SOL-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

SOL_data = yf.download(SOL_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

doge_df = pd.DataFrame(SOL_data)

# Define the Excel file path

excel_file_path = “SOL_historical_data.xlsx”

# Save the data to an Excel sheet

SOL_df.to_excel(excel_file_path, sheet_name=”SOL_historical_data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the Solana (SOL)

Figure 4 below gives the evolution of the Solana (SOL) returns from April, 2020 to December 31, 2023 on a daily basis.

Figure 4. Evolution of the Solana (SOL) returns.

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Solana (SOL)

The R program that you can download above also allows you to compute summary statistics about the returns of the Solana (SOL). Table 2 below presents the following summary statistics estimated for the Solana (SOL):

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 2. Summary statistics for Solana (SOL).

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Solana (SOL) returns

Historical distribution

Figure 5 represents the historical distribution of the Solana (SOL) daily returns for the period from April, 2020 to December 31, 2023.

Figure 5. Historical Solana (SOL) distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from April, 2020 to December 31, 2023.

Figure 6 below represents the Gaussian distribution of the Solana (SOL) daily returns with parameters estimated over the period from April, 2020 to December, 2023.

Figure 6. Gaussian distribution of the Solana (SOL) returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Solana (SOL) returns

The R program that you can download above also allows you to compute risk measures about the returns of the Solana (SOL).

Table 3 below presents the following risk measures estimated for the Solana (SOL):

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 3. Risk measures for the Solana (SOL).

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the Solana (SOL) while the study of the right tail is relevant for an investor holding a short position in the Solana (SOL).

Why should I be interested in this post?

This blog offers an engaging exploration into a cryptocurrency that transcends traditional finance, appealing to a wide audience due to its cultural relevance, investment potential, and vibrant community. Solana’s reputation for high performance in blockchain technology, boasting the capability to process thousands of transactions per second, makes it an appealing option for developers and users seeking efficient transaction processing. Moreover, staying updated on Solana can offer insights into the growth of its ecosystem, including the development of decentralized applications (dApps) and strategic partnerships. For investors, Solana’s increasing popularity and ecosystem growth may signal investment opportunities, making it worthwhile to track news and discussions surrounding the platform. Additionally, Solana’s innovative technical advancements in scalability, consensus mechanisms, and developer tools are of interest to those intrigued by blockchain technology. Engaging with the Solana community provides opportunities for networking and gaining valuable insights into this rapidly expanding ecosystem.

Related posts on the SimTrade blog

About cryptocurrencies

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

   ▶ Snehasish CHINARA How to get crypto data

   ▶ Alexandre VERLET Cryptocurrencies

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

   ▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for Solana

CoinMarketCap Historical data for Solana

About the author

The article was written in April 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).
Posted in Contributors | Tagged , , , , , | Leave a comment

Bitcoin est un rêve, un idéal, un espoir

Bitcoin est un rêve, un idéal, un espoir

Jean-Marie Choffray

Dans cet article, Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology) introduit son recent article “Mille quatre cent milliards de dollars”.

Personne ne sait précisément ce qu’est Bitcoin (avec « Bvle réseau). Au plan conceptuel, bitcoin (avec « b le jeton) est une chaîne, aussi indestructible que possible, de blocs d’enregistrements, aussi sécurisés que possible. Cette technologie nouvelle est donc un projet en cours dont personne ne peut préjuger l’avenir, quelle que soit la dimension considérée. Bitcoin deviendra ce que la majorité de ses utilisateurs décidera, et surtout aura le courage, d’en faire. Pour Satochi Nakamoto, c’était un rêve. Pour ceux qui travaillent aujourd’hui sur son code, c’est un idéal. Enfin, pour ceux qui l’utiliseront demain, c’est un espoir. L’Histoire de l’Humanité, une autre chaîne de blocs d’enregistrements – à l’évidence, non sécurisés et falsifiables ! – , s’apparente au reflet d’une montée de la Conscience individuelle et collective (cf. « Le phénomène humain » de Pierre Teilhard de Chardin). Bitcoin, c’est L’espoir maintenant (entretien entre Jean-Paul Sartre et Benny Lévy) : « une tension vers la fin, que l’échec, le tragique ne sauraient annuler… La valeur économique de bitcoin serait-elle le prix de la liberté ?

   ▶ Lire l’article Bitcoin est un rêve, un idéal, un espoir

Autres articles sur le blog

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

   ▶ Jean-Marie CHOFFRAY Mille quatre cent milliards de dollars

A propos de l’auteur

L’article a été rédigé en mars 2024 par Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology).

Posted in Contributors, Financial techniques | Tagged , | Leave a comment

Types of Market Consensus

Types of Market Consensus

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) explains what are the market consensus and different forms of into financial sentiments.

Introduction

Market consensus often talked about in financial circles, goes beyond just a collective opinion; it reflects how investors feel and what’s happening in the financial world. This article looks into different types of market consensus: the agreement on prices between buyers and sellers, the insights provided by financial analysts who study companies’ basics and economic indicators, and the views of technical analysts who analyze stock prices. Several things affect market consensus, like how people generally feel about the market, expectations for market changes, and the actions of important players like central banks.

Understanding the various forms of market consensus is essential for investors and traders navigating the complex world of finance. These collective opinions shape market trends and impact investment decisions.

Price Consensus

One of the most visible forms of market consensus is reflected in asset prices. The principle of supply and demand drives prices, with consensus emerging as traders and investors assess the value of an asset based on various factors such as economic indicators, company performance, and geopolitical events. As these factors change and influence perceptions, they contribute to the evolving consensus reflected in asset prices.

Example: In 2020, Tesla’s stock experienced a tremendous surge as market consensus shifted positively around electric vehicles and renewable energy. Investors believed in the company’s potential for growth, leading to a significant increase in Tesla’s stock price.

Market consensus by financial analysts

Consensus on revenues and earnings

Earnings consensus revolves around the expected future earnings of a company. Analysts and financial experts often provide earnings estimates, and market consensus forms around these forecasts. Deviations from these expectations can lead to significant price movements as investors reassess the company’s performance and prospects. This dynamic interaction between earnings forecasts and market reactions underscores the importance of consensus expectations in shaping investor sentiment and market behavior.

Example: Apple’s quarterly earnings announcements are highly anticipated by the market. If Apple reports earnings that exceed analysts’ consensus estimates, it can lead to a surge in its stock price, reflecting the positive earnings consensus.

Consensus on economic indicators

Economic indicators, such as GDP growth, inflation rates, and unemployment figures, shape the macroeconomic consensus. Governments, central banks, and international organizations routinely release data that analysts and investors leverage to assess the broader economic landscape. Market responses frequently track deviations from consensus forecasts related to these indicators. When actual economic data diverges from expectations, it can trigger significant market movements as investors adjust their outlook on economic conditions and potential policy responses.

Example: During the global financial crisis of 2008, there was a consensus among economists that the world economy was entering a recession. This consensus influenced investor behavior, leading to widespread selling in equity markets and a shift towards safer assets.

Market consensus by technical analysts

Market consensus by technical analysts revolves around interpreting stock price movements and patterns to forecast future market trends. Technical analysts use charts and indicators to identify potential buying or selling opportunities based on historical price data. By analyzing patterns such as support and resistance levels, moving averages, and trading volumes, technical analysts contribute insights into market sentiment and potential price directions. This approach to market consensus complements fundamental analysis and provides a different perspective on investor behavior and sentiment. Breaking through a significant resistance level might lead to a bullish consensus; similarly, breaking through a significant support level might lead to a bearish consensus.

Factors influencing the market consensus

Size of the company and coverage by financial analysts

The size of a company and how many analysts are covering it also influence the stock market consensus. If only a handful of analysts are assigned to the stock, the market consensus estimates are more likely to vary from actual results.

Market sentiment

The sentiment of market participants plays a crucial role in shaping market consensus. Investor sentiment can be bullish or bearish, influenced by factors like news, social media, and market events. Contrarian investors often excel by taking positions opposite to prevailing sentiment, capitalizing on opportunities arising from market overreactions and sentiment shifts. Understanding and analyzing market sentiment is essential for gauging potential market directions and identifying contrarian investment opportunities.

Example: The GameStop saga in early 2021 is a notable example of sentiment consensus. Retail investors on social media forums collectively drove up the stock price of GameStop, challenging traditional market dynamics and catching institutional investors off guard.

Volatility expectations

Volatility expectations, measured by metrics like the VIX (Volatility Index), represent a form of consensus about future market stability. Traders and investors use volatility as an indicator of market risk, and consensus around heightened volatility can lead to defensive strategies, such as increased hedging or reduced risk exposure. Understanding and interpreting volatility consensus is essential for adapting investment strategies to prevailing market conditions and risk perceptions.

Example: The COVID-19 pandemic in 2020 led to a consensus on increased market volatility. The VIX (Volatility Index) surged as investors anticipated heightened uncertainty, prompting shifts in investment strategies to account for the expected market fluctuations.

Policy Consensus

Central bank policies, government regulations, and fiscal measures contribute to policy consensus. Market participants closely monitor statements and decisions made by central banks and governments, forming expectations about interest rates, monetary policy, and regulatory changes. Any surprises in these areas can lead to market volatility.

Example: The announcement of the U.S. Federal Reserve’s quantitative easing policies during the 2008 financial crisis influenced market consensus. The expectation of increased liquidity and lower interest rates contributed to a rally in stock markets.

Technological Consensus

Technological consensus refers to the collective agreement or perception within the technology sector regarding emerging trends, innovations, or the adoption of specific technologies. Industry experts, analysts, and stakeholders contribute to this consensus through assessments of technology developments, market dynamics, and consumer behavior. Consensus within technology influences investment decisions, product development strategies, and market forecasts. Understanding technological consensus is crucial for businesses and investors seeking to navigate the rapidly evolving landscape of technology-driven industries.

Example: The rise of FAANG stocks (Facebook, Apple, Amazon, Netflix, Google) in the last decade reflects a technological consensus. Investors collectively believed in the transformative power of these technology giants, contributing to their substantial market capitalizations.

Conclusion

Market consensus, when explored through the lens of data and statistics, transforms from a theoretical concept to a tangible and actionable tool. Whether you’re an investor, a business leader, or an analyst, integrating statistical insights into your understanding of market consensus adds a layer of precision to decision-making. In the dynamic world of finance, where every percentage point matters, harnessing the power of market consensus with a data-driven approach ensures a more informed and strategic navigation of financial waters.

Why should I be interested in this post?

In essence, this article provides a holistic and data-driven perspective on market consensus, catering to the interests of investors, business professionals, and anyone seeking a nuanced understanding of how collective sentiments shape the financial landscape. Whether you’re actively involved in financial decision-making or simply intrigued by the dynamics of the market, this article offers valuable insights that bridge theory and real-world applications.

Related posts on the SimTrade blog

   ▶ Aamey MEHTA Market efficiency: the case study of Yes bank in India

   ▶ Louis DETALLE The importance of data in finance

Useful resources

CNN Fear & Greed Index: What emotion is driving the market now?

Market consensus What is market consensus?

Faster Capital Navigating Markets: The Power of Market Analysis and Consensus Estimates

About the author

The article was written in April 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole – Master in Management (MiM), 2021-2024).
Posted in Contributors, Financial techniques | Tagged | Leave a comment

Job description – Financial analysts

Job description – Financial analysts

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) explains the job of financial analysts and their contributions to the investment community.

Introduction

Financial analysts serve as the backbone of the finance industry, providing critical insights and analysis to support investment decisions. Did you know that the Bureau of Labor Statistics in the US projected a 6% growth in employment of financial analysts from 2020 to 2030, faster than the average for all occupations? According to a survey by the CFA Institute (November 2021), most financial analysts believe that their role is becoming increasingly important in today’s complex financial landscape.

This article explores the multifaceted role of financial analysts, with a particular focus on their responsibilities and contributions within both the buy-side and sell-side sectors of the financial industry. Buy-side analysts work for entities that have money to invest, such as mutual funds, hedge funds, pension funds, and high-net-worth individuals. Sell-side analysts work for brokerage firms, investment banks, and other entities that sell investment services. These analysts conduct research and analysis on companies and industries to publish investment recommendations for the firm’s clients and the general investing public.

What Does a Financial Analyst Do?

Financial analysts analyze a firm’s past financial data to spot trends and assess risks, which helps them predict outcomes for business decisions, identify sale or purchase opportunities, and make investment recommendations. To that end, a financial analyst may need to work with different types of data such as company financial statements, the performance of investments such as stocks and bonds, industry research, macroeconomic data, and more, depending upon the specific role they play within the organization.

Buy-Side Financial Analysts: Crafting Investment Strategies

Buy-side analysts work for entities that have money to invest, such as mutual funds, hedge funds, pension funds, and high-net-worth individuals. The job of a financial analyst is important as these financial institutions manage a lot of money. For example, the global assets under management (AUM) of hedge funds amounted to approximately $3.6 trillion in 2020 (Gitnux, December 16, 2023). These analysts perform research and analysis to make direct investment decisions on behalf of their firm’s money. Their primary objective is to identify and capitalize on lucrative investment opportunities that align with their client’s objectives and risk profiles.

Role and responsibilities

Buy-side financial analysts are instrumental in evaluating and recommending alternative investment opportunities to their clients. More and more, they take into consideration the environmental, social, and governance (ESG) factors that are important in their investment decision-making process.

Examples of companies employing Buy-Side Financial Analysts

An investment manager at BlackRock specializes in infrastructure investments and identifies Brookfield Infrastructure Partners L.P. (NYSE: BIP) as a promising opportunity for long-term growth and income generation. BlackRock’s investment in Brookfield Infrastructure Partners helps diversify its clients’ portfolios and provides stable returns over time.

Sell-Side Financial Analysts: Providing Market Insights and Advisory Services

Did you know that the global investment banking revenue reached $124.5 billion in 2020, driven by strong performance in equity underwriting and mergers and acquisitions (M&A) advisory? Sell-side financial analysts work for brokerage firms, investment banks, and financial advisory companies. Their role revolves around providing research and advisory services to institutional and retail investors, as well as corporate clients.

Role and responsibilities

A survey by the Brunswick group found that institutional investors believe that the quality of sell-side research reports has improved over the past five years. Sell-side financial analysts play a crucial role in providing timely and insightful research reports to help clients make informed investment decisions.

Examples of companies employing Sell-Side Financial Analysts:

  • A sell-side analyst at Goldman Sachs publishes a research report on Amazon.com Inc. (NASDAQ: AMZN), recommending a “buy” rating based on its dominant position in e-commerce and cloud computing, as well as its consistent revenue growth. This recommendation attracts significant investor interest and contributes to a surge in Amazon’s stock price.
  • An equity research analyst at J.P. Morgan advises Alphabet Inc. (NASDAQ: GOOGL) on strategic options for expanding its autonomous driving technology division, conducting industry analysis and financial modeling to support the recommendations. Alphabet Inc. leverages J.P. Morgan’s expertise to develop a comprehensive growth strategy for its autonomous driving business.
  • A sell-side analyst at Vanguard conducts extensive research on emerging technology companies and recommends investing in Tesla Inc. (NASDAQ: TSLA), recognizing its leadership in electric vehicles and sustainable energy solutions. This recommendation leads to a significant increase in Tesla’s stock price, generating substantial returns for Vanguard’s clients.

Financial analysts play a pivotal role in shaping investment strategies, providing market insights, and facilitating financial transactions. Whether operating on the buy-side or sell-side, these professionals leverage their analytical expertise and industry knowledge to navigate the complexities of the financial markets. By offering investment recommendations, conducting research, and providing advisory services, financial analysts contribute significantly to the pursuit of financial prosperity and wealth creation.

Skills and Qualifications

Now given the job and the daily environment they have to deal with there are certain skills a financial analyst would need to have. Soft skills such as Analytical Thinking, Communication Skills, Attention to Detail, and Time Management hard skills such as Technology Skills, Quantitative Skills, Financial Analysis, and Industry Knowledge are demanded.

When it comes to the career path of an analyst, requires them to stay updated on industry developments, regulations, and best practices. From various analyses and surveys, we could say that many financial analysts hold a bachelor’s degree in finance, accounting, economics, or a related field. Pursuing a master’s degree in finance, business administration (MBA), or a specialized finance program can provide additional knowledge and credentials.

Obtaining certifications such as the Chartered Financial Analyst (CFA) designation is common in the financial industry. The CFA program covers a broad range of topics including investment analysis, portfolio management, and ethics, and is highly regarded in the field. Apart from the theoretical knowledge gaining practical experience through internships or entry-level positions at financial institutions, investment firms, or corporate finance departments is essential for building foundational skills and industry knowledge.

  • The Chartered Financial Analyst (CFA) designation is highly valued in the buy-side industry. Buy-side financial analysts need to possess strong data analysis skills to extract actionable insights from large datasets and alternative data sources. They play a crucial role in developing and implementing these customized investment strategies.
  • Sell-side financial analysts need to possess strong academic credentials and technical skills to excel in their roles. They believe that soft skills such as communication and relationship-building are essential for success in their roles. Sell-side financial analysts need to effectively communicate their research findings and build rapport with clients to gain their trust and confidence.

Remuneration

According to a report by Bloomberg, the average compensation for equity research analysts at investment banks in the United States ranged from $200,000 to $600,000 in 2020, depending on their level of experience and performance. Sell-side financial analysts are well-compensated for their expertise in analyzing and recommending investment opportunities to clients.

Why should I be interested in this post?

In essence, this article provides a perspective on the job of financial analysts. For a student who would like to work in finance, it is important to know about the job of a financial analyst as it relates to both the corporate world and financial markets.

Related posts on the SimTrade blog

   ▶ Aamey MEHTA Market efficiency: the case study of Yes bank in India

   ▶ Louis DETALLE The importance of data in finance

   ▶ Louis DETALLE Bloomberg

Useful resources

Forbes Financial Analyst Job Description

Gitnux Must-Know Hedge Fund Statistics

CFA Survey of CFA Institute members on latest ESG matters

Brunswickgroup About the Brunswick Digital Investor Survey

Market consensus What is market consensus?

Faster Capital Navigating Markets: The Power of Market Analysis and Consensus Estimates

About the author

The article was written in April 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Posted in Contributors, Finance jobs | Leave a comment

Institutional Brokers’ Estimate System (IBES)

Institutional Brokers’ Estimate System (IBES)

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) presents Institutional Brokers’ Estimate System (IBES), which provides market consensus for the financial community.

Introduction

In the fast-paced world of finance, the Institutional Brokers’ Estimate System, commonly known as IBES (often written as “I/B/E/S.”), stands as a linchpin in providing investors, analysts, and financial professionals with reliable forecasts and estimates.

IBES, with its roots in comprehensive data aggregation, takes center stage in providing a panoramic view of financial analysts’ estimates and forecasts. IBES acts as a centralized repository of earnings estimates, revenue projections, and other key financial metrics, serving as a vital resource for investors seeking actionable insights.

History

IBES was created in 1976 by the investment research firm, Lynch, Jones & Ryan (LJR). It was developed to address the need for a centralized system to collect and distribute earnings estimates from brokerage analysts. The database offers historical data from its inception and extends internationally from 1987. Over the years, IBES went through several ownership changes. In 1988, LJR was acquired by Primark Corporation. Primark Corporation later merged with Thomson Financial Services in 1990, and IBES became part of Thomson Financial. Thomson Financial subsequently merged with Reuters Group in 2008 to form Thomson Reuters. Thus, IBES became a part of Thomson Reuters. Then Thomson Reuters was acquired by private equity firm Blackstone Group and rebranded as Refinitiv in 2018. Refinitiv was later acquired by the London Stock Exchange Group (LSEG) in 2020. Therefore, IBES is currently owned by the London Stock Exchange Group (LSEG) through its subsidiary, Refinitiv.

Key Components of IBES

Earnings Estimates

IBES compiles earnings estimates from a multitude of financial analysts, providing a consensus view on the expected earnings of a company. As of the latest data, it aggregates forecasts from over 16,000 analysts worldwide, providing a robust consensus on expected earnings for companies across the globe.

Revenue Projections

Beyond earnings, IBES includes revenue projections, offering a comprehensive view of a company’s expected top-line growth. Analysts’ forecasts are aggregated to provide a consensus estimate, aiding investors in gauging revenue expectations.

Forecasts for Key Financial Metrics

IBES extends beyond earnings and revenue, encompassing a spectrum of financial metrics. This includes estimates for operating margins, cash flows, and other key indicators, providing a holistic view of analysts’ expectations. The sheer volume of data—covering over 18,000 companies—ensures a comprehensive snapshot of financial expectations.

Coverage

There are certain types of coverage when we are talking about data coverage such as the Number of Companies Covered, geographic Coverage, Market Capitalization Coverage, Industry Coverage, Depth of Coverage, and Historical Coverage.

According to LSEG data analytics, I/B/E/S Estimates data is displayed at the company level, screened with rigorous quality control methods across more than 23,400 active companies in more than 90 countries, and sourced from over 19,000 analysts.

Estimates Data from over 950 firms contribute data to I/B/E/S, from the largest global houses to regional and local brokers, with U.S. data back to 1976 and international data back to 1987.

Period

IBES has evolved since its introduction in 1976 and includes international data from 1987. I/B/E/S Global Aggregates, with over 30 years of history, facilitates top-down analysis to better assess potential growth and risk as well as future value across industry, sector, index, country, and region.

Frequency

Initially focusing on annual earnings estimates, the database subsequently broadened to encompass quarterly earnings forecasts.

Firms and Financial analysts

IBES covers a wide range of firms across different industries, sectors, and regions. This includes companies listed on major stock exchanges in numerous countries and markets around the world. 950+ contributors, across 90+ in developed and emerging markets, totaling over 19,000 individual analysts – the most in the industry. Unmatchable history across more than 60,000 companies back to 1976 for North America, 1987 for other markets.

Pricing

The specific pricing for accessing I/B/E/S data is not explicitly mentioned on the IBES website and you have to make a request through the LSEG website which manages IBES. The cost likely varies based on the package and offerings selected, which can include different data sets, access methods, and service frequencies. For detailed pricing information, it’s recommended to directly contact LSEG or the respective service providers you’re interested in, as they can provide more precise details based on your specific requirements and the scale of your intended use.

For academic and non-commercial research purposes, access might be available through institutional subscriptions with specific terms of use, as seen with Aalto University’s subscription financed by the Aalto University Data Hub for its users. This indicates that the availability and cost of I/B/E/S data may vary significantly based on the type of use and the access platform. For precise pricing and package options, directly contacting the service providers is the best approach.

Use of IBES by the Financial Community

Benchmark for Analysis

IBES serves as a benchmark for investors and analysts, quantifying market reactions, it dives into the numbers behind market reactions. According to Faster Capital, studies reveal that stocks experiencing positive earnings surprises, surpassing IBES estimates, tend to outperform the market. These numerical insights underscore the practical implications of aligning investment decisions with IBES consensus.

Market Expectations

Analysts and fund managers utilize IBES to gauge market expectations for specific companies. Understanding consensus estimates aids in forming investment strategies aligned with prevailing market sentiments.

Earnings Season Preparation

During earnings seasons, IBES becomes a critical tool for investors preparing for companies’ financial releases. It provides a consolidated view of analysts’ forecasts, helping investors assess potential surprises or disappointments.

IBES and Tests of Market Efficiency

Academic works

The data was subsequently used as the basis for articles in academic finance journals attempting to demonstrate that changes in consensus earnings estimates could identify opportunities to capture excess returns in subsequent periods.

Information Dissemination

IBES plays a pivotal role in disseminating timely information. As estimates are constantly updated based on new information, IBES ensures that market participants have access to the latest insights, contributing to market efficiency.

Pros and Cons

Given its history and operations in huge industries and markets, we certainly need to know the pros and cons of the IBES estimates. In terms of accuracy metrics, IBES relies on the accuracy of analysts’ forecasts. Statistical metrics, such as the mean absolute error (MAE), offer a quantitative evaluation of the system’s precision.

Conclusion

IBES, when viewed through a data-driven lens, transforms into more than a system and becomes a useful tool for decision-makers navigating the intricacies of financial markets.

Why should I be interested in this post?

In essence, this article discovers how the global data powerhouse, backed by impactful statistics, empowers investors, providing a data-driven lens into market expectations and offering actionable insights for informed decision-making in the dynamic world of finance.

Related posts on the SimTrade blog

   ▶ Aamey MEHTA Market efficiency: the case study of Yes bank in India

   ▶ Louis DETALLE The importance of data in finance

   ▶ Bijal GANDHI Earnings per share

Useful resources

London Stock Exchange Group (LSEG) I/B/E/S Estimates

Wikipedia Institutional Brokers’ Estimate System

Market consensus What is market consensus?

Faster Capital Navigating Markets: The Power of Market Analysis and Consensus Estimates

About the author

The article was written in March 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).
Posted in Contributors, Financial news, Financial techniques | Tagged , | Leave a comment

My Experience as an Investment Intern at Eurazeo

My Experience as an Investment Intern at Eurazeo

Dante Marramiero

In this article, Dante MARRAMIERO (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2020-2023) presents its professional experience in Euazeo, a European leading Private Equity based in Paris.

About Eurazeo

Eurazeo stands as a prominent European firm within the world of alternative investments, boasting a diversified portfolio within various investment strategies, including private debt, real Estate, venture, growth, small-mid buyout, and mid-large buyouts. Eurazeo was initially the family office of the Lazard Freres family, but in 2018 decided to merge with Idinvest in order to start fundraising capital from third parties. Following 2018, Eurazeo’s strategy has always been to reduce the balance sheet investments and to increase the third-party capital investments.

Logo of the company.
Logo of  Eurazeo
Source: the company.

Internship Overview

During my time as an Investment Intern at Eurazeo from January 2023 to June 2023, I had the privilege to immerse myself in the intricacies of private equity and alternative investments. My internship included a range of responsibilities aimed at supporting Eurazeo’s investment initiatives. My department was “Direct Transactions” and during my internship, I participated actively in three different activities:

Syndication of Co-Investment Opportunities

I actively participated in the syndication process of four co-investment opportunities across various investment strategies including private debt, growth, and mid-large buyout. This involved conducting comprehensive due diligence, financial analysis, and market research to assess the viability and potential returns of each opportunity. Together, these co-investment opportunities accounted for approximately €750 million in total investment value, underscoring Eurazeo’s commitment to strategic partnerships and collaborative investment initiatives. Co-investments, theoretically speaking can be cataloged under direct transactions as SPV (Special Purpose Vehicle) are created specifically for one single transaction and you are not making the investment for the limited partners but you are making it with the LPs (Limited Partners).

Strategic SPV Structures Analysis

I was tasked with examining strategic Special Purpose Vehicle (SPV) structures solutions for potential investment opportunities. This entailed analyzing, comparing, and developing alternative fundraising structures such as Collateral Fund Obligation and Rated Feeder Fund, focusing on optimizing capital deployment and mitigating risk. The main reason why we were evaluating new financial structures was to attract a category investor that, at the time, was not willing to invest in our funds: American insurance companies. 2023 has been generically speaking a rough year for fundraising capital and for this reason, we decided to implement this kind of solution. A collateral fund obligation is a structure composed by certified debt and equity; this structure will invest in different funds (all managed by Eurazeo) and will have the advantage of using the leverage raised as certified debt to enhance the return on the investment and the Cash on Cash. Therefore, by evaluating various SPV structures, we aimed to enhance our flexibility in structuring investments and optimizing returns for our investors, by using the right amount of leverage.

Evaluation of Secondary Transactions Advisors

I had the opportunity to participate in two competitive selection processes for secondary transaction advisors, tasked with choosing the financial advisor to support us in executing a single asset continuation vehicle. The evaluation process included analyzing and comparing proposed solutions, assessing current market conditions, and evaluating alignment with Eurazeo’s investment strategy and objectives.

Furthermore, this project included evaluation and due diligence, intending to identify strategic partners capable of delivering value-added solutions and maximizing returns for our investors. Single asset continuation vehicles are specialized structures tailored for investments held within the portfolio of a current fund of the firm. These investments require divestment as limited partners seek liquidity. However, recognizing the potential upside, the firm decides to establish these vehicles.

What did I learn during this experience?

My internship at Eurazeo provided invaluable opportunities for skills and knowledge development across various areas:

  • Financial Analysis: I honed my skills in financial modeling, valuation techniques, and investment analysis through hands-on experience with real-world investment opportunities.
  • Due Diligence: I gained practical insights into the due diligence process, including a thorough examination of financial statements, market trends, and competitive landscapes.
  • Strategic Thinking: I developed a strategic mindset by evaluating investment opportunities within the broader context of Eurazeo’s investment thesis and long-term objectives.
  • Communication and Collaboration: I enhanced my communication and collaboration skills through interaction with cross-functional teams and external stakeholders, fostering effective teamwork and decision-making.

This internship therefore offered a unique opportunity to gain firsthand experience in the dynamic and fast-paced world of private equity and alternative investments. As an aspiring finance professional, this experience has equipped me with the skills, knowledge, and insights necessary to thrive in the competitive landscape of the investment industry. Moreover, it has reaffirmed my passion for finance and deepened my understanding of the critical role played by alternative investment firms in driving economic growth and value creation.

As a newcomer to the finance industry, I had not anticipated the level of intricacy and competition inherent within the environment of Eurazeo. The depth of analysis, the meticulous attention to detail, and the relentless pursuit of excellence underscored the caliber of professionals operating within the firm. Despite the initial surprise, I found myself invigorated by the intellectual rigor and spirited competition that permeated every facet of Eurazeo’s operations.

Central to my experience at Eurazeo was the discovery of a challenging yet remarkably cohesive team—a team that demanded nothing short of excellence yet fostered an environment of camaraderie and mutual support. The intensity of our collaborative efforts forged bonds that transcended professional boundaries, culminating in a shared sense of purpose and accomplishment. Indeed, within the crucible of challenging assignments and tight deadlines, I discovered that the true measure of an internship lies not merely in the tasks accomplished but, in the relationships, forged and the personal growth attained.

Long But Fulfilling Working Hours

While the demands of the internship necessitated long hours and unwavering dedication, I found solace in the gratifying pursuit of knowledge and skill refinement. On average, my workday extended until around 10:30 in the evening, with occasional instances requiring weekend office visits. Despite the rigors of the schedule, the sense of fulfilment derived from contributing to meaningful projects and engaging with industry experts mitigated the challenges posed by extended working hours.

A game-changing internship

My internship at Eurazeo stands as a transformative chapter in my professional journey, characterized by unexpected challenges, profound growth, and enduring camaraderie. Through immersion in the fast-paced realm of private equity, I have gained invaluable insights, honed essential skills, and cultivated enduring relationships that will undoubtedly shape my future endeavours. As I reflect on my time at Eurazeo, I am reminded that true growth emerges from embracing adversity, fostering meaningful connections, and steadfastly pursuing excellence—lessons that will continue to guide me on the path toward personal and professional fulfillment.

Why should I be interested in this post?

I aspire that this experience might aid other students intrigued by Private Equity in gaining deeper insights into the internal dynamics and the range of exposure one can encounter within a private equity firm. Often, when students hear about private equity, their minds jump straight to financial analysis and modeling, overlooking the broader scope. My aim is for this article to spark curiosity among students about this sector, encouraging them to explore the private equity market further.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Chloé ANIFRANI My experience as an Asset Management Sales Assistant for Amplegest

   ▶ Alexandre VERLET Classic brain teasers from real-life interviews

   ▶ Matisse FOY Key participants in the Private Equity ecosystem

   ▶ Lilian BALLOIS Discovering Private Equity: Behind the Scenes of Fund Strategies

Useful resources

Eurazeo

Bain Bain private Equity Report 2023

About the author

The article was written in April 2024 by Dante MARRAMIERO (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2020-2023)

Posted in Contributors, Professional experiences | Tagged , , , | Leave a comment

Doge Coin: Unraveling the Phenomenon of the Internet’s Favourite Crypt

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the evolution of the most popular memecoin, Dogecoin.

 Snehasish CHINARA

Historical context and background

Dogecoin, a cryptocurrency that started as a joke, quickly evolved into a significant player in the world of digital assets. Created in December 2013 by software engineers Billy Markus and Jackson Palmer, Dogecoin was initially intended to satirize the hype surrounding cryptocurrencies at the time. The coin’s logo features the Shiba Inu dog from the “Doge” meme, which was immensely popular on the internet during that period. Despite its humorous origins, Dogecoin gained traction due to its welcoming and inclusive community, as well as its low transaction fees and fast confirmation times.

The early days of Dogecoin saw rapid adoption and a vibrant online community rallying around the coin. It gained attention for its philanthropic efforts, including fundraising campaigns to sponsor charity events and support causes such as building water wells in developing countries and sponsoring Olympic athletes. These initiatives helped distinguish Dogecoin from other cryptocurrencies and fostered a sense of community among its users.

Over time, Dogecoin’s popularity continued to grow, fueled in part by endorsements from notable figures such as Elon Musk, who frequently tweeted about the coin, further amplifying its visibility. Despite facing occasional security issues and challenges, Dogecoin has persevered, becoming one of the most recognized and traded cryptocurrencies in the market. Its unique blend of humor, community spirit, and accessibility has endeared it to a wide range of users, making it a significant player in the ever-expanding crypto landscape.

Doge Coin Logo

Source: Yahoo! Finance.

Figure 1. Key Dates in Doge Coin History

Source: Yahoo! Finance .

Key features

    Decentralization

    Like most cryptocurrencies, Dogecoin operates on a decentralized network, meaning it is not controlled by any single entity or organization. Transactions are recorded on a public ledger known as the blockchain, which is maintained by a network of nodes.

    Scrypt Algorithm

    Dogecoin uses the Scrypt algorithm for its proof-of-work consensus mechanism, which is less energy-intensive compared to Bitcoin’s SHA-256 algorithm. This allows for greater accessibility to mining for individuals with standard computer hardware.

    Fast Transactions

    Dogecoin boasts relatively fast transaction times, with blocks being mined approximately every minute. This makes it suitable for quick and efficient transfers of value.

    Low Transaction Fees

    Transaction fees on the Dogecoin network are typically minimal, making it cost-effective for transferring even small amounts of value.

    Meme Culture

    Dogecoin’s branding and marketing heavily leverage internet meme culture, particularly the “Doge” meme featuring the Shiba Inu dog. This playful and approachable branding sets Dogecoin apart from other cryptocurrencies and contributes to its widespread appeal.

Use cases

    Tipping

    Dogecoin gained popularity early on for its use as a tipping currency on social media platforms like Reddit and Twitter. Users can easily send small amounts of Dogecoin to content creators or other users as a form of appreciation.

    Charitable Donations

    The Dogecoin community has a history of supporting charitable causes and disaster relief efforts. Dogecoin has been used to raise funds for various initiatives, including sponsoring athletes, funding clean water projects, and aiding during natural disasters.

    E-commerce

    Some online merchants and retailers accept Dogecoin as a form of payment for goods and services. This includes businesses ranging from small independent shops to larger e-commerce platforms.

    Micropayments

    Dogecoin’s low transaction fees and fast confirmation times make it suitable for micropayments, allowing users to easily transfer small amounts of value online.

    Community Engagement

    Dogecoin continues to serve as a vehicle for community engagement and participation. Its lighthearted and inclusive nature fosters a sense of camaraderie among its users, who often come together for events, fundraisers, and online discussions.

    Experimental Projects

    Developers and enthusiasts sometimes use Dogecoin for experimental projects or to explore new applications of blockchain technology. These projects can range from art and gaming to decentralized finance (DeFi) experiments.

Technology and underlying blockchain

Dogecoin operates on a blockchain-based technology similar to Bitcoin and many other cryptocurrencies. It employs a decentralized peer-to-peer network that relies on nodes spread across the globe to validate and record transactions. Dogecoin’s blockchain uses the Scrypt hashing algorithm, which was initially designed to facilitate quicker confirmation times compared to Bitcoin’s SHA-256 algorithm. This choice of algorithm allows for a more accessible mining process, enabling individuals with standard computer hardware to participate in securing the network and earning rewards. Transactions on the Dogecoin network are grouped into blocks, which are then added to the blockchain through a process known as mining. Miners compete to solve complex mathematical puzzles, and the first miner to solve a puzzle validates the transactions in a block and adds it to the blockchain. Dogecoin’s block time is approximately one minute, resulting in faster transaction confirmations compared to Bitcoin’s ten-minute block time. Additionally, Dogecoin originally had a limitless supply, with a fixed reward of 10,000 DOGE per block; however, this changed in 2014 to an inflationary model, where a fixed number of coins are added to the supply each year. This combination of technology and economic design contributes to Dogecoin’s unique characteristics and its appeal within the cryptocurrency ecosystem.

Supply of coins

Dogecoin’s supply dynamics are distinctive within the cryptocurrency landscape. Initially launched with no hard cap on its total supply, Dogecoin features an inflationary issuance model designed to maintain a steady influx of coins into the market. Unlike Bitcoin’s fixed supply of 21 million coins, Dogecoin’s issuance rate started at 5 billion coins per year and gradually decreases over time. This inflationary nature ensures a continuous supply of Dogecoin, theoretically allowing for ongoing miner rewards and a sustained incentive for network participation. However, it’s worth noting that while the supply of Dogecoin is technically infinite, the rate of new coin creation diminishes over time, resulting in a decreasing inflation rate and a more stable supply trajectory. This unique supply mechanism distinguishes Dogecoin from many other cryptocurrencies and can influence its long-term economic dynamics and utility as a medium of exchange or store of value.

Historical data for Doge Coin

How to get the data?

The Doge Coin is popular cryptocurrency on the market, and historical data for the Doge Coin such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for Doge Coin on Yahoo! Finance (the Yahoo! code for Doge Coin is Doge-USD).

Figure 2. Doge Coin data

Source: Yahoo! Finance.

Historical data for the Doge Coin market prices

Since its inception in 2013, Dogecoin has experienced notable price fluctuations, driven by a combination of factors including market speculation, community engagement, and broader trends in the digital asset space. Initially launched as a joke currency, Dogecoin’s price remained relatively stable for several years, trading at fractions of a cent. However, its price surged dramatically in early 2021, fueled by social media hype and celebrity endorsements, reaching all-time highs of over 70 cents per coin. This unprecedented rally brought Dogecoin into the spotlight, attracting widespread attention from investors and media outlets. Despite subsequent price corrections, Dogecoin has maintained a prominent position in the cryptocurrency market, with its price influenced by various factors including Elon Musk’s tweets, meme culture, and broader market sentiment. Overall, the historical price evolution of Dogecoin exemplifies the volatile and dynamic nature of the cryptocurrency market, highlighting the interplay between community enthusiasm, market speculation, and broader industry trends.

Figure 3 below represents the evolution of the price of Doge Coin in US dollar over the period November 2018 – December 2022. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 3. Evolution of the Doge Coin price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Doge Coin.

Download R file

Data file

The R program that you can download above allows you to download the data for the Doge Coin from the Yahoo! Finance website. The database starts on October, 2018.

Table 1 below represents the top of the data file for the Doge Coin downloaded from the Yahoo! Finance website with the R program.

Table 1. Top of the data file for the DOGE Coin

Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Download the Python code for USD Coin data

Python script to download Doge historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for Doge Coin

doge_ticker = “DOGE-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

doge_data = yf.download(doge_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

doge_df = pd.DataFrame(doge_data)

# Define the Excel file path

excel_file_path = “DOGE_historical_data.xlsx”

# Save the data to an Excel sheet

doge_df.to_excel(excel_file_path, sheet_name=”DOGE_historical_data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download

Evolution of the Doge Coin

Figure 4 below gives the evolution of the Doge Coin on a daily basis.

Figure 4. Evolution of the DOGE Coin Figure 5 below gives the evolution of the Doge Coin returns from November, 2018 to December 31, 2022 on a daily basis.

Figure 5. Evolution of the Doge Coin returns.

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Doge Coin

The R program that you can download above also allows you to compute summary statistics about the returns of the Doge Coin. Table 2 below presents the following summary statistics estimated for the Doge Coin:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 2. Summary statistics for Doge Coin.

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Doge Coin returns

Figure 6 represents the historical distribution of the Doge Coin daily returns for the period from November, 2018 to December 31, 2022.

Figure 6. Historical Doge Coin distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from October, 2018 to December 31, 2022. Figure 7 below represents the Gaussian distribution of the Ethereum daily returns with parameters estimated over the period from October, 2018 to December, 2022.

Figure 9. Gaussian distribution of the Doge Coin returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Doge Coin returns

The R program that you can download above also allows you to compute risk measures about the returns of the Doge Coin.

Table 3 below presents the following risk measures estimated for the Doge Coin:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 3. Risk measures for the Doge Coin.

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the XRP while the study of the right tail is relevant for an investor holding a short position in the Doge Coin.

Why should I be interested in this post?

This blog offers an engaging exploration into a cryptocurrency that transcends traditional finance, appealing to a wide audience due to its cultural relevance, investment potential, and vibrant community. From its origins as a meme coin to its remarkable price movements, understanding Dogecoin’s dynamics provides valuable insights into both the cryptocurrency market and internet culture. Delving into its technological underpinnings, community engagement, and market trends offers a concise yet comprehensive overview of Dogecoin’s significance in the evolving landscape of digital currencies.

Related posts on the SimTrade blog

About cryptocurrencies

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

   ▶ Snehasish CHINARA How to get crypto data

   ▶ Alexandre VERLET Cryptocurrencies

   ▶ Youssef EL QAMCAOUI Decentralised Financing

   ▶ Hugo MEYER The regulation of cryptocurrencies: what are we talking about?

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

   ▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for Doge Coin

CoinMarketCap Historical data for Doge Coin

About the author

The article was written in March 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).
Posted in Contributors | Tagged , , , , , | Leave a comment

USD Coin: Deep Dive into  the Role of Stablecoins in Modern Finance

 Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the stable coin USD Coin.

Historical context and background

USD Coin (USDC) is a type of cryptocurrency known as a stablecoin, designed to maintain a stable value relative to the US dollar (USD). It was launched in September 2018 by Centre Consortium, a collaboration between cryptocurrency exchange Coinbase and blockchain technology company Circle. The primary goal of USDC is to provide a digital asset that can be easily transferred between users and used for transactions, while minimizing the volatility typically associated with other cryptocurrencies like Bitcoin or Ethereum.

The need for stablecoins like USDC arose due to the inherent volatility of many cryptocurrencies. While Bitcoin and other digital assets have gained significant attention and adoption, their prices can fluctuate dramatically over short periods, which can make them less practical for everyday transactions and financial contracts. Stablecoins like USDC offer a solution to this problem by pegging their value to a stable asset, such as the US dollar, thereby providing stability and predictability for users.

USDC operates on the Ethereum blockchain as an ERC-20 token, making it compatible with a wide range of decentralized applications (dApps) and enabling seamless integration with the broader cryptocurrency ecosystem. This infrastructure allows users to easily send and receive USDC tokens across various platforms and services, including exchanges, wallets, and payment processors.

Since its launch, USDC has seen significant growth in adoption and usage. It has become one of the most widely used stablecoins in the cryptocurrency market, with billions of dollars worth of USDC tokens in circulation. Its stability and liquidity have made it a popular choice for traders, investors, and businesses looking to transact in digital assets without exposure to the volatility of other cryptocurrencies.

USD Coin Logo

Source: Yahoo! Finance.

Figure 1. Key Dates in USDC History

Source: Yahoo! Finance.

Key features

Stability

USD Coin is a stablecoin, meaning it is pegged to the value of the US dollar on a 1:1 basis. This stability is maintained through regular audits and backing by reserves of US dollars held in custody by regulated financial institutions.

Transparency

USDC operates on blockchain technology, providing transparency and immutability of transactions. Every USDC token is backed by an equivalent number of US dollars held in reserve, which is regularly audited and transparently reported to ensure trust among users.

Speed and Efficiency

Transactions involving USDC can be executed quickly and efficiently on blockchain networks, enabling near-instantaneous settlement compared to traditional banking systems, which may take days for cross-border transactions.

Global Accessibility

USDC enables borderless transactions, allowing users to send and receive payments globally without the need for intermediaries such as banks. This accessibility empowers individuals and businesses, particularly in regions with limited access to traditional financial services.

Interoperability

USDC is compatible with various blockchain platforms and protocols, including Ethereum, Algorand, and Solana, among others. This interoperability facilitates its integration into a wide range of decentralized applications (DApps) and decentralized finance (DeFi) ecosystems.

Use cases

Remittances and Cross-Border Payments:

USDC provides a cost-effective and efficient solution for remittance payments and cross-border transactions, enabling individuals and businesses to transfer value across borders quickly and securely without the need for traditional banking intermediaries.

Stable Value Storage

Due to its stable value pegged to the US dollar, USDC serves as a reliable store of value and a hedge against volatility in the cryptocurrency market. Users can hold USDC as a stable asset to preserve purchasing power and mitigate the risks associated with price fluctuations in other cryptocurrencies.

Decentralized Finance (DeFi) Applications

USDC is widely used as a liquidity provider and collateral asset in various DeFi protocols and applications such as decentralized exchanges (DEXs), lending platforms, yield farming, and liquidity pools. Users can leverage USDC to earn interest, borrow assets, or participate in yield farming strategies within the DeFi ecosystem.

Commerce and Payments

Merchants and businesses can accept USDC as a form of payment for goods and services, leveraging its fast transaction settlement times and low transaction fees compared to traditional payment methods. Integrating USDC payments can streamline cross-border commerce and reduce friction associated with fiat currency conversions.

Financial Inclusion

USDC plays a crucial role in expanding financial inclusion by providing access to digital financial services for individuals and communities underserved by traditional banking infrastructure. By utilizing blockchain technology and stablecoins like USDC, individuals without access to traditional banking services can participate in the global economy and access a wide range of financial products and services.

Technology and underlying blockchain

USD Coin (USDC) operates on a blockchain-based infrastructure, primarily leveraging the Ethereum blockchain as its foundation. Utilizing Ethereum’s smart contract functionality, USDC tokens are issued, transferred, and redeemed in a transparent and trustless manner. The ERC-20 standard, a set of rules and protocols defining interactions between tokens on the Ethereum network, governs the behavior of USDC tokens, ensuring compatibility with a wide range of wallets, exchanges, and decentralized applications (DApps). Moreover, USDC employs a consortium model for governance and operation, with regulated financial institutions serving as members responsible for the issuance, custody, and redemption of USDC tokens. These institutions adhere to strict regulatory compliance measures and conduct regular audits to verify that each USDC token is fully backed by an equivalent reserve of US dollars held in custody. This combination of blockchain technology, smart contracts, and regulatory oversight ensures the integrity, transparency, and stability of USD Coin, making it a trusted and widely adopted stablecoin within the cryptocurrency ecosystem.

ERC-20 Standard of Ethereum for USD Coin

The ERC-20 standard, short for Ethereum Request for Comment 20, is a widely adopted technical specification governing the creation and implementation of fungible tokens on the Ethereum blockchain. Introduced by Fabian Vogelsteller and Vitalik Buterin in 2015, ERC-20 defines a set of rules and functions that enable seamless interoperability between different tokens, ensuring compatibility with various decentralized applications (DApps) and wallets. Tokens adhering to the ERC-20 standard are characterized by a consistent set of methods, including transfer, balance inquiry, and approval mechanisms, facilitating easy integration and widespread adoption across the Ethereum ecosystem. This standardization has played a pivotal role in the proliferation of tokenization, empowering developers to create diverse tokenized assets, conduct crowdfunding campaigns through Initial Coin Offerings (ICOs), and establish decentralized exchanges (DEXs) where ERC-20 tokens are traded autonomously. Additionally, ERC-20 compliance enhances security and interoperability, fostering trust and usability within the Ethereum network.

Supply of coins

The supply dynamics of USD Coin (USDC) are governed by its underlying smart contract protocol and the management of its issuer, Centre Consortium, a collaboration between Circle and Coinbase. USDC operates on a principle of full backing, where each USDC token issued is backed by an equivalent number of US dollars held in reserve. This backing ensures a 1:1 peg to the US dollar, maintaining its stability. The issuance and redemption of USDC are facilitated through regulated financial institutions that hold the corresponding fiat reserves. Moreover, USDC’s supply is transparently audited on a regular basis, with attestations provided by reputable auditing firms to verify the adequacy of reserves. Through these mechanisms, the supply of USDC remains elastic, expanding or contracting based on market demand while preserving its stability and trustworthiness as a stablecoin in the digital asset ecosystem.

Historical data for USDC

How to get the data?

The USDC is popular cryptocurrency on the market, and historical data for the USDC such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for USDC on Yahoo! Finance (the Yahoo! code for USD Coin is USDC-USD).

Figure 2. USD Coin data

Source: Yahoo! Finance.

Historical data for the USD Coin market prices

The historical market price of USD Coin (USDC) has remained relatively stable, as its primary function is to maintain a value pegged to the US dollar at a 1:1 ratio. Since its inception, USDC has consistently traded around the $1 mark, with minor fluctuations typically attributed to market dynamics and liquidity conditions. Investors and traders often utilize USDC as a safe haven asset or a means of temporarily exiting volatile cryptocurrency markets, contributing to its stability. This stability has made USDC a preferred choice for individuals and institutions seeking to hedge against cryptocurrency volatility or facilitate seamless transitions between digital and fiat currencies. Additionally, the transparent backing of USDC by reserves of US dollars held in custody by regulated financial institutions further enhances market confidence and contributes to its stable market price over time.The historical market price of USD Coin (USDC) has remained relatively stable, as its primary function is to maintain a value pegged to the US dollar at a 1:1 ratio. Since its inception, USDC has consistently traded around the $1 mark, with minor fluctuations typically attributed to market dynamics and liquidity conditions. Investors and traders often utilize USDC as a safe haven asset or a means of temporarily exiting volatile cryptocurrency markets, contributing to its stability. This stability has made USDC a preferred choice for individuals and institutions seeking to hedge against cryptocurrency volatility or facilitate seamless transitions between digital and fiat currencies. Additionally, the transparent backing of USDC by reserves of US dollars held in custody by regulated financial institutions further enhances market confidence and contributes to its stable market price over time.

Figure 3 below represents the evolution of the price of USD Coin in US dollar over the period Oct 2018 – Dec 2022. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 3. Evolution of the USD Coin price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the USD Coin.

Download R file

Data file

The R program that you can download above allows you to download the data for the USD Coin from the Yahoo! Finance website. The database starts on Oct, 2018. Table 1 below represents the top of the data file for the USD Coin downloaded from the Yahoo! Finance website with the R program.

Table 1. Top of the data file for the USD Coin

Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Download the Python code for USD Coin data

Python script to download USD Coin historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for USD Coin

usdc_ticker = “USDC-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

usdc_data = yf.download(usdc_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

usdc_df = pd.DataFrame(usdc_data)

# Define the Excel file path

excel_file_path = “USDC_historical_data.xlsx”

# Save the data to an Excel sheet

usdc_df.to_excel(excel_file_path, sheet_name=”USDC Historical Data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the USD Coin

Figure 4 below gives the evolution of the USDC on a daily basis.

Figure 4. Evolution of the USD Coin.

Source: computation by the author (data: Yahoo! Finance website).

Figure 5 below gives the evolution of the USD Coin returns from Oct, 2018 to December 31, 2022 on a daily basis.

Figure 5. Evolution of the USD Coin returns

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the USD Coin

The R program that you can download above also allows you to compute summary statistics about the returns of the USD Coin. Table 2 below presents the following summary statistics estimated for the USD Coin:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 2. Summary statistics for USDC.

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the USD Coin returns

Historical distribution

Figure 6 represents the historical distribution of the USD Coin daily returns for the period from Oct, 2018 to December 31, 2022.

Figure 6. Historical USDC distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from October, 2018 to December 31, 2022.

Figure 7 below represents the Gaussian distribution of the USD Coin daily returns with parameters estimated over the period from October, 2018 to December, 2022.

Figure 7. Gaussian distribution of the USDC returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the USD Coin returns

The R program that you can download above also allows you to compute risk measures about the returns of the USD Coin.

Table 3 below presents the following risk measures estimated for the USD Coin:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 3. Risk measures for the USDC.

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the XRP while the study of the right tail is relevant for an investor holding a short position in the XRP.

Why should I be interested in this post?

The post offers an opportunity for both newcomers and seasoned cryptocurrency enthusiasts to delve into the concept of stablecoins, gaining insights into how digital assets maintain stability amidst market volatility. Furthermore, the post highlights USDC’s role in fostering financial inclusion by enabling borderless transactions, appealing to readers passionate about democratizing finance. Additionally, exploring USDC’s significance in the burgeoning realm of decentralized finance (DeFi) could intrigue those interested in innovative financial technologies and investment opportunities. Examining USDC’s historical performance and market dynamics can offer valuable insights for investors and traders, while shedding light on its compliance measures and regulatory landscape can address concerns regarding legal risks, contributing to readers’ understanding and confidence in this digital asset.

Related posts on the SimTrade blog

About cryptocurrencies

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

   ▶ Snehasish CHINARA How to get crypto data

   ▶ Alexandre VERLET Cryptocurrencies

   ▶ Youssef EL QAMCAOUI Decentralised Financing

   ▶ Hugo MEYER The regulation of cryptocurrencies: what are we talking about?

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

   ▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for USDC

CoinMarketCap Historical data for USDC

About the author

The article was written in March 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Posted in Contributors, Financial news, Financial techniques | Tagged , , , , , | Leave a comment

Private Banks : Treasuries Departments and proprietary asset allocation

Private Banks : Treasuries Departments and proprietary asset allocation

Quentin CHUZET

In this article, Quentin CHUZET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023) explains about Private banks Treasuries Departments and the challenges of proprietary asset allocation.

Introduction

Within the Treasury Department of a Private Bank, the role of its employees is to record incoming and outgoing cash flows, as well as to direct the allocation of assets that comprise its Treasury. Thus, on one hand, we find the amount of cash on the asset side, and on the other hand, on the liability side, the amount of client deposits. In other words, it can be said that the Treasury is primarily constituted by the various deposits made by clients.

These are grouped into 2 categories: sight deposits (money visible in the client’s bank account, available and usable at any time) and term deposits (money placed generally in interest-bearing accounts but only available once the placement has matured).

Private Bank balance sheet
Private Bank balance sheet
Source: La Finance Pour Tous

To address performance and revenue challenges, the Treasury department manages cash by investing it in interest-bearing products, aiming to generate significant margins. This activity, performed by the Middle and Front Office teams, is referred to as proprietary trading or prop asset allocation.

Before the 2008 financial crisis, the regulatory environment was less stringent, granting banks greater freedom in risk management. However, the crisis highlighted the dangers of this approach, leading to a significant strengthening of regulations.

In 2013, Basel III introduced one of the most important regulatory agreements in banking. It aims to enhance the resilience of banks by increasing their capital and liquidity requirements. Basel III notably introduced a short-term liquidity ratio (LCR) and a long-term liquidity ratio (NSFR).

Regarding liquidity, private banks must now hold sufficient liquid assets to withstand mass deposit withdrawals. They must also comply with a liquidity coverage ratio (LCR), requiring them to have enough high-quality liquid assets to cover their net cash outflows over a 30-day period.

In terms of solvency, private banks must now comply with a capital adequacy ratio (Cooke ratio), requiring them to have sufficient capital to absorb potential losses. Basel III also introduced a leverage ratio, limiting banks’ leverage.

To ensure compliance with these new regulatory frameworks while continuing to maximize revenue, banks have implemented treasury policies and control ratios to define limits and mitigate risks. These treasury policies, spanning multiple pages, guide Front Office teams in asset allocation to maintain the most efficient risk/return ratio possible. It is important to note that each bank has its own risk level, hence treasury policies and their respective limits may vary from one bank to another.

In general, a bank tends to favor a very low-risk level by prioritizing assets that can be quickly liquidated while limiting exposure to interest rate fluctuations or certain sectors. In the risk management process, liquidity and solvency ratios are monitored, as well as ratios related to interest rate risk and non-systematic risk.

Treasury Policy

These Treasury policies, spanning multiple pages, guide Front Office teams in asset allocation to maintain the most efficient risk/return ratio possible. It is important to note that each Bank possesses a risk level unique to itself, which is why Treasury Policies and their constituent limits may vary from one to another.

Thus, this document is divided into several limits and control ratios aimed at protecting against incurred risks. Among the main ratios present in the Treasury Policies, we find:

Liquidity and solvability ratios

Among liquidity and solvability ratios, controls are placed on the recovery time of securities held by the Treasury, with constraints notably regarding recoverable assets within 2 days and those recoverable within 30 days. Through these ratios, the average lifespan of the portfolio is controlled as well as the maximum duration of the securities, as well as the portion of assets placed with the Central Bank, ensuring a high rate of return in periods of high rates and near-immediate liquidity, as it is possible to recover from one day to the next.

These ratios aim to protect against the greatest risk a bank may face: that of illiquidity. This risk is heightened during crises and when clients wish to make massive withdrawals. The bank must thus ensure that all liquidity can be returned.

Security portfolio allocation’s ratios

Through these ratios, the Bank adheres to exposure limits by sector, industry, or company outlined in the Treasury policy: the leverage ratio is a significant indicator. This allows for diversification of allocations and investments and thus frees from specific risk. There are also control ratios based on Moody’s, S&P, and Fitch ratings or ESG ratings.

Finally, there are also ratios aimed at calculating the share represented by each asset class. It should be noted that each asset class represents what is called a “position” in the Treasury Sheet. In other words, each different class represents a different line. Among these lines are placements in the Money Market (Bond Portfolio, NEUCP Portfolio, placements in OPC funds), term interbank loans, currency and rate SWAPs, etc.

Sensitivity ratios

Through these ratios, the Treasury department controls the sensitivity to rates faced by Treasury assets. The Treasury Policy indicates threshold limits that should not be exceeded to ensure optimal rate adjustments, in the event of both increases and decreases.

Risk Management and Asset Allocation

Managing liquidity and solvability risk

To manage liquidity risk as effectively as possible, Private Banks can consider various strategies:

  • Purchase securities eligible for ECB refinancing
  • Maintain a high proportion of assets placed at the Central Bank on a daily basis (as they are highly liquid and yield interest at times of high interest rates).
  • Maintain a short maturity of the security portfolio and short-term deposits.

Interest-rate risk management

Interest-rate risk is a major issue for Private Banks, since a change in interest rates would have a major impact on the yield and price of bond holdings. The sensitivity of an asset represents the length of time during which it cannot be subjected to a variation in its interest rate. Thus, depending on the prevailing trend surrounding interest rate movements, Treasury Traders must invest to maintain a balanced sensitivity ratio. For example, in a scenario where the market strongly expects a future rate decrease, a strategy aimed at maximizing the adjustment period to the rate and thus the sensitivity ratio may be the best option. Conversely, in a scenario where the market anticipates a significant rate hike in the upcoming period, reducing the adjustment period to the rate for the portfolio would allow a quick re-indexing to a higher rate and reduce the time during which those assets would be “under-earning”.

Specific risk and diversification

A specific risk is linked to a particular event, affecting a single company, a sector of activity or a specific financial instrument. It differs from systemic risk, which affects the entire financial system. To reduce this risk, diversification is a key element, which is why a Private Bank can specify limits by sector or asset class in its Treasury Policy.

Therefore, the Treasury department of the Bank and its Front Office teams can allocate their assets to government bonds, as well as to corporate bonds in sectors such as retail, energy, or Real Estate.

Conclusion

In conclusion, the challenges of asset allocation within the Treasury of private banks are manifold. Guided by Treasury Policies, limits, and control ratios, it must adapt to the emergence of a new regulatory environment to define low-risk, high-liquidity investment strategies while addressing performance and revenue maximization objectives. Furthermore, proprietary asset allocation drives private banks to enhance their internal resources and develop tailored management tools.

Why should I be interested in this post?

If you’re interested in proprietary asset management, or in the workings of a treasury department within a private bank, you’ll find a first overview of these topics in this article.

If you have any questions about the position or the sector, please don’t hesitate to contact me on my personal Linkedin page, I’ll be delighted to answer them.

Related posts on the SimTrade blog

   ▶ Youssef LOURAOUI Asset Allocation Techniques

   ▶ Akshit GUPTA Asset Allocation

   ▶ Youssef LOURAOUI Equity Market Neutral Strategy

Useful resources

La Trésorerie active d’une entreprise

Banque-Trésorerie

Le Bilan d’une banque

Liquidité, solvabilité et crise bancaire : quelles relations ?

Diversification et gestion des risques

Les placements d’une Trésorerie d’entreprise

Le risque de taux

About the author

The article was written in March 2024 by Quentin CHUZET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023).

Posted in Contributors, Financial techniques | Leave a comment

My experience as Revenue Analyst at Olympique de Marseille

My experience as Revenue Analyst at Olympique de Marseille

Quentin CHUZET

In this article, Quentin CHUZET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023) shares his professional experience as Revenue Analyst at Olympique de Marseille.

About the company

Olympique de Marseille is a French football club founded in 1899. It is one of the most emblematic clubs in French and European football history, with an emblematic international reputation. Through decades of performance and media exposure, it has become an emblem of French sport, inscribing itself as a culture and tradition for millions of supporters around the world.

Logo of the Olympique de Marseille
Logo of Olympique de Marseille
Source: Olympique de Marseille.

Its takeover by the Mc Court Group in 2016 initiated a radical change in management and in the harmonization of processes, to continue to broaden its scope and enable grows bigger. Therefore, the club generates more than 200m € for the seasons 2021-2022 and 2022-2023 with 270m € of revenues expected for the season 2023-2024 It bases its growth on the sporting aspect but also on innovative sport business strategies. With a stadium capacity surpassing any of other Ligue 1 club (67.000 seats) and a meticulous ticketing strategy, the club is part of the Top 10 of the most attractive stadiums in Europe and continues to capitalize on its national and European reach.

OM Revenues vs other clubs.
OM Revenues vs others – Deloitte Report
Source: Deloitte Football Benchmark.

My apprenticeship

Joining Olympique de Marseille allowed me to discover and evolve within the soccer ecosystem, but also to take a practical approach to issues relating to football clubs revenues optimization and maximization.

The diversity of revenue sources at a club like Olympique de Marseille opens the door to a wide range of missions and tasks. As I was directly involved in all strategic aspects of revenue management : I was notably involved in defining the pricing of Ticketing & Hospitality (VIP) revenue streams, drawing up business plans for club projects, managing budgets and revenue targets set at the start of the season, analyzing financial opportunities represented by the entry of sponsors or investors, etc.

I therefore occupied a strategic role, acting as a pivot between the sales and finance teams, defining budgets alongside management control and that could be reachable for the commercial team, and while supporting the sales teams in achieving the latter by analyzing revenue opportunities and proposing strategic recommendations.

1/4 French Cup, season 2022-2023 : OM-Annecy. Historical record of attendance for a ¼ in the club’s and competition’s history.
Velodrome OM Annecy
Source: Olympique de Marseille.

My missions

Strategic recommendations and pricing

The main task assigned to a Revenue Analyst at Olympique de Marseille is to play an active role in defining pricing for the general public and VIPs at each match. To do this, I had to identify the exogenous variables of each match and quantify their impact in order to measure inbound demand as a function of a certain price level. Using historical data from similar matches and cross-referencing it with the maximization opportunities available at any given moment, I was responsible for drawing up the pricing and sales strategy (choosing best commercialization timing, best offer to address etc.) calculating forecast revenue trends and presenting my recommendations to management on several occasions. Thanks to our strategy the club reached the total of 1.550.000 attenders for a unique season and broke other records as the highest attendance ever known for one game (65.984 attendees vs PSG), the highest average attendance for one season (62.065 attendees), the highest number of sold-out games (23 over the season) and the highest attendance ever known for a French Cup game (63.929 attendees). Finally, the strategies leaded by the Revenue Management department leaded to a 4.8M € maximization of the total club revenues.

Participation in club project profitability studies

More generally, as a Revenue Analyst, I was involved in every aspect of the club’s revenue development.

Conducting pricing analysis and manage commercial strategy was part of the Ticketing & Hospitality revenue stream. However, my missions also involved providing my vision on certain high-stakes projects involving additional revenue generation. From the arrival of potential sponsors and investors to the launch of the new “Peuple Bleu&Blanc” loyalty program, I was responsible for measuring the profitability of these projects by calculating the potential income they could generate, while defining and steering a strategy for maximizing it.

Intermediary role between sales and finance teams

The role was multi-functional in terms of strategy, finance, and sales. We had to define ambitious, realistic budgets alongside management control, while supporting the sales teams in achieving them. To do this, we analyzed revenue opportunities and proposed appropriate strategic recommendations for the Ticketing, Hospitality, Retail, Membership and other revenue streams.

Development of steering tools and reporting dashboards

As the analysis are based almost entirely on the measurement of KPIs (Key Performance Indicators), the development of management tools represented a major challenge. So, it was up to me to play an active part, working with the IT (Information Technology) and back-office teams.

Required skills and knowledge

In my role at Olympique de Marseille, it is crucial to understand the financial and commercial issues facing the club and its teams. It’s also important to develop a strategic way of thinking in which everything can be optimized.

As a Revenue Analyst, every recommendation needs to be backed up by data, and every opportunity must be quantified to support each recommendations. That’s why you need to have an excellent mind for analyzing and interpreting data.

Furthermore, the numerous presentations and reports to management require solid written and oral communication skills (PowerPoint presentations, e-mail reports, etc.), as well as adaptability to the person you’re talking to, in order to make the right points and get your recommendations accepted.

In addition, mastery of Excel and the budgeting/revenue forecasting process is key to this position. As each decision has a significant impact on the season’s revenues, numerous budget forecasts are required, particularly around Best/Mid/Worst scenarios. It is also necessary to master the Power BI tool (Business Intelligence by Microsoft) to be able to develop and interpretate every KPI.

Finally, it is essential to be humble and questioning in order to identify areas for improvement in each strategy, and to meet management’s requirements on an ongoing basis and know how to identify the best practices of these recommendations.

OM revenues details for the 2022/2023 season.
OM Revenues - Deloitte Report
Source : Deloitte Report

Financial concepts related to my apprenticeship

Budget Management

Budget management is a key concept in this position, influencing the decisions of sales teams and having a major impact on every strategy implemented. Budget management represents a guideline for costs and revenues, and in particular the preparation of a forecast budget which serves as a basis for input management.

Revenue Management

Revenue Management is a key concept which consists of defining variables considered to have an impact on maximizing revenues in periods of growth and limiting losses in periods of decline. For a club such as Olympique de Marseille, this means capitalizing on positive trends (good sporting dynamics, special matches, etc.) and protecting revenues when the sportive situation is non-favorable : succession of bad games, bad weather on matchday, non-attractive game due to opponent.

Business Plans and Financial modeling

Studying the profitability of projects and simulating the impact of commercial strategies involves drawing up business plans and financial models in order to calculate forecast revenues. To do this, we need to establish different scenarios adapted to different contexts and KPIS and then take into account the action and development plans for these projects, as well as the business models used.

Why should I be interested in this post?

If you’re interested in the field of Finance and Strategy, particularly within a soccer club, then this article will give you a clearer picture of the tasks and skills required, as well as the importance of Revenue Management within a sporting institution. Through this empowering experience, I was able to develop both the hard skills that will serve me well in my future career in Finance, and the soft skills that will enable me to perform in a demanding, high-pressure environment.

If you have any questions about the position or the sector, please don’t hesitate to contact me on my personal Linkedin page, I’ll be delighted to answer them.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Bijal GANDHI Revenue

   ▶ Medine ACAR Mon expérience professionnelle en tant que contrôleuse de gestion chez Carfuel

Useful resources

Official OM website

Deloitte reporting : Football Money League 2024 edition

Official French Football League website : All DNCG report until 2021-2022 season

Example of a Football club balance sheet : SC Bastia (French 1st division) during the 2015-2016 season

About the author

The article was written in March 2024 by Quentin CHUZET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2019-2023).

Posted in Contributors, Professional experiences | Leave a comment

Mille quatre cent milliards de dollars

Mille quatre cent milliards de dollars

Jean-Marie Choffray

Dans cet article, Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology) introduit son recent article “Mille quatre cent milliards de dollars”.

L’événement fondateur du XXe siècle est la première guerre mondiale, conséquence de rivalités politiques et économiques entre les puissances de l’Alliance et celles de l’Entente. Dix millions de civils et de militaires meurent. Vingt millions sont blessés. Mais, pour la première fois, une institution internationale est créée dans le but de régler les différends internationaux : la Société des Nations (SDN).

L’événement fondateur du XXIe siècle pourrait être la production en 2009 du premier bloc de transactions du réseau Bitcoin et, accessoirement, l’échange du premier bitcoin. Aucun mort. Aucun blessé. Mais, pour la première fois, un réseau informatique décentralisé permet d’enregistrer irréversiblement et de certifier irrévocablement tous types de transactions entre des intervenants souhaitant garder l’anonymat. En termes simples, un bitcoin est une copie numérique exploitable – i.e. conservable et échangeable – d’une série (chaîne) complète et indestructible de transactions sécurisées. Leur nombre est exponentiellement limité dans le temps (le dernier exemplaire sera produit vers 2140) et dans l’espace (vingt et un millions au total). Le réseau Bitcoin est en quelque sorte la « Banque Centrale » d’un écosystème numérique multipolaire dont seuls les utilisateurs contrôlent le devenir. Personne ne peut prévoir la diversité des applications que cette technologie autorise, ni les transformations qu’entrainera sa diffusion dans les secteurs où la fiabilité et la validité de l’information et des connaissances sont essentielles. Sa capitalisation boursière le rendrait-elle indestructible ? Pour un investisseur averti : ignorer Bitcoin, c’est se tirer une balle dans le pied… Et, tout miser sur Bitcoin, c’est se tirer une balle dans la tête !

   ▶ Lire l’article Mille quatre cent milliards de dollars

Autres articles sur le blog

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

A propos de l’auteur

L’article a été rédigé en mars 2024 par Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology).

Posted in Contributors, Financial news | Leave a comment

Venture Capital 101: A Quick Overview

Venture Capital 101: A Quick Overview

Alessandro MARRAS

In this article, Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023) gives a quick overview of Venture Capital.

What is Venture Capital?

Venture capital (VC) is a specialized form of financing where investors provide funds to startup or early-stage companies with high growth potential. This funding is crucial for startups to develop and expand their business operations. Venture capitalists not only provide financial support but also offer expertise and guidance to help these companies succeed. The goal of venture capital is to generate significant returns by investing in innovative businesses that have the potential to disrupt markets and achieve substantial growth.

VCs have five main functions:

  • They serve as financial intermediaries, channeling capital from investors into promising portfolio companies.
  • Their investments are directed towards private companies, making them illiquid assets.
  • VCs actively participate in the management and oversight of their portfolio companies, embodying active investors.
  • The primary objective of VCs is to maximize financial returns, typically through strategic exits like acquisitions or IPOs.
  • VCs prioritize investments in entrepreneurial ventures with substantial growth potential, aiming to foster internal growth and increase the likelihood of successful exits. These characteristics highlight the dynamic and strategic nature of venture capital investments, contributing to innovation and economic growth.

VCs vs others:

  • VCs differ from angel investors as they function as financial intermediaries rather than investing personal funds directly.
  • Unlike mutual or hedge funds, VCs invest specifically in private companies, placing them within the category of private equity and alternative investments.
  • While all VCs are private equity funds, the inverse isn’t true; not all private equity funds engage in venture capital.
  • VCs set themselves apart from crowdfunding platforms by actively participating in the companies they invest in, providing ongoing monitoring and management support.

How are VCs organized?

Venture capital firms are typically organized as limited partnerships, structured to facilitate investment activities while providing a degree of protection and incentive for both investors and managers. For investors this protection comes in the form of limited liability, meaning their risk of losing money is confined to their investment amount and they are not personally liable for the debts of the business. This allows them to invest in high-risk ventures with a capped downside. For managers the incentive is often structured as carried interest, a share of the profits of the investments, which aligns their financial interests with the success of the firm’s investments. This ensures that managers are motivated to select and nurture companies that will yield high returns, thereby directly linking their compensation to their performance in managing the venture capital firm’s portfolio.

Limited partnerships in venture capital consist of two main categories of partners. Firstly, there are limited partners, who contribute capital to the fund and bear limited liability. These investors can include wealthy individuals, banks, mutual funds, and other institutional investors. Secondly, there is the general partner, responsible for managing the fund’s operations and investments, and who assumes unlimited liability. Figures like Don Valentine, Ben Horowitz, and Peter Thiel are examples of notable general partners in the venture capital industry.

The lifespan of a typical limited partnership in venture capital is around ten years, during which investors’ capital is committed and cannot be withdrawn. General partners receive compensation in the form of a management fee and a share of the profits generated by successful investments, known as carried interest.

Limited partnerships offer tax efficiency, as they are not subject to corporate taxes, with partners instead paying taxes on their share of the profits. Additionally, distributions of securities to partners incur no immediate tax implications, with taxes only due upon the eventual sale of the securities.

This organizational structure provides a framework that incentivizes efficient investment management and aligns the interests of both limited and general partners in achieving successful outcomes.

Benefits of VC

Venture capital offers a range of benefits to both entrepreneurs and investors, fostering innovation, driving economic growth, and facilitating wealth creation. Firstly, venture capital provides crucial funding to startups and early-stage companies that may otherwise struggle to secure financing from traditional sources such as banks or public markets. This injection of capital enables entrepreneurs to pursue ambitious ideas and develop groundbreaking technologies, driving innovation across various industries. Moreover, venture capitalists often bring valuable expertise, networks, and mentorship to the table, helping startups navigate challenges, refine their business strategies, and accelerate their growth trajectory.

Secondly, venture capital plays a pivotal role in job creation and economic development. By supporting high-growth startups, venture capital investments fuel job creation, as these companies expand their operations, hire new talent, and contribute to local economies. Additionally, successful startups can spawn entire ecosystems of suppliers, service providers, and complementary businesses, further stimulating economic activity and driving regional prosperity.

Furthermore, venture capital investment offers attractive returns for investors willing to accept the inherent risks associated with early-stage ventures. While venture capital investments carry a higher risk of failure compared to traditional investments, they also offer the potential for substantial returns on successful exits, such as acquisitions or initial public offerings (IPOs). As a result, venture capital serves as a vital asset class for investors seeking diversification and opportunities for outsized returns in their investment portfolios.

VC Financing Cycle

The Venture Capital Financing Cycle delineates the sequential stages of funding that startups typically undergo, from inception to exit. This cycle starts with the Seed Stage, where initial capital is raised to prove concepts and build prototypes. As the startup matures, it may progress through various rounds of funding—Angel, Series A, Series B, and beyond—each designed to fuel growth, product development, market expansion, and operational scaling. The Bridge stage serves as a critical juncture for preparing more mature startups for substantial future rounds or positioning for exit strategies. The cycle culminates in the Pre-IPO and IPO Preparation stages, where companies ready themselves for public offering or seek acquisition opportunities, marking the exit phase. This framework not only structures the investment landscape but also maps the growth trajectory of startups. The VC financing cycle is emblematic of the symbiotic relationship between investors seeking to maximize returns and startups in need of capital to fuel their growth ambitions, fostering innovation and economic development within the broader ecosystem.

VCs financial performance in 2023

In 2023, the venture capital (VC) market experienced significant shifts, reflecting broader economic challenges and evolving investment trends. The year saw a considerable downturn in VC investments, dropping to the lowest levels in four years, with a year-over-year decrease of 35% from the already declining levels of 2022. The total amount raised by VC-backed startups barely surpassed $140 billion, influenced notably by a few mega-deals in the artificial intelligence (AI) sector. The decline was not just in the amount raised but also in deal volume across nearly all fund classes, reaching the lowest point in a decade. Later-stage investments saw the most significant reduction in dollar volume quarter-over-quarter, while Series A investments showed some resilience with a 9% increase.

The backdrop of economic headwinds, valuation concerns, and an overhang of more than 50,000 existing VC-backed startups created a challenging environment for new investments. VC fund formation also experienced a sharp decline, dropping 62% from the record year in 2022, although there was a slight uptick in the last quarter of the year. This situation has led to increased caution among venture capitalists, with a notable reluctance to engage in mega-round financing. Only 50 mega deals were recorded in the last quarter of 2023, marking the lowest total since 2017.

Despite these challenges, AI continued to garner significant attention and investment, driving many of the largest deals in the U.S. during the last quarter of 2023. This trend suggests that while the overall VC investment has declined, specific sectors, particularly those related to technological innovation and AI, continue to attract substantial interest and funding.

Why should I be interested in this post?

As an ESSEC students interested in finance, this post can be a useful resource due to its relevance in the financial sector. Understanding venture capital offers insights into alternative investments, career opportunities in private equity, and the dynamics of financing innovative startups, enriching your knowledge and potential career paths within the finance industry.

Related posts on the SimTrade blog

   ▶ Louis DETALLE A quick presentation of the Private Equity field…

   ▶ Louis DETALLE A quick review of the Venture Capitalist’s job…

   ▶ Marie POFF Film analysis: The Wolf of Wall Street

Useful resources

Zider B. (1998) How Venture Capital Works Harvard Business Review.

Jeffrey Grabow (29/01/2024) Will venture capital market rebound in 2024 or seek new floor? EY

KPMG Venture Pulse Q4 2023

Deloitte 2024 trends in venture capital

About the author

The article was written in March 2024 by Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023).

Posted in Contributors, Financial techniques | Leave a comment

Top 5 Private Equity firms

Top 5 Private Equity firms

Alessandro MARRAS

In this article, Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023) presents the top 5 Private Equity firms globally.

Introduction

In the dynamic landscape of finance, private equity firms wield significant influence driving innovation, growth, and value creation. These firms are renowned for their strategic investments and operational expertise, generating substantial returns for investors. In this post, we embark on a journey to uncover the top 5 Private Equity firms globally guided by specific metrics that underscore their reputation and success.

Methodology

To define the top 5 global Private Equity firms, we developed a methodology rooted in a detailed selection process and comprehensive data analysis. Given the vast landscape of private equity firms, our first step was to narrow down our focus by seeking rankings from reputable independent research institutes, such as Private Equity International and Forbes. These rankings served as a benchmark, helping us identify firms that consistently garnered recognition for their excellence within the industry.

From these rankings, we selected firms that appeared most frequently in the top 5, ensuring that our pool consisted of widely acknowledged and respected entities. This approach enabled us to narrow down our analysis to a manageable number of firms, facilitating a more in-depth assessment of their performance and standing.

With our selection criteria in place, we turned to publicly listed firms, as their annual reports provide accessible data crucial for our analysis. It is important to understand that being publicly listed means that the private equity firm is listed on stock exchanges, and anyone can buy shares in the company. However, this is a big difference from investing in private equity funds, where the capital raised is used to buy portfolio companies.

From this we obtained the 5 firms to rank:

  • Blackstone Inc.
  • KKR & Co Inc.
  • The Carlyle Group Inc.
  • Apollo Global Management, Inc.
  • TPG Inc.

To rank these firms, we will be guided by essential measurement metrics that illuminate their standing and impact within the industry. Our evaluation method hinges on key indicators, including Assets Under Management (AUM), fundraising totals, and performance metrics such as gross returns. From an investor’s perspective, this comprehensive approach ensures a deep understanding of each firm’s financial health, strategic positioning, and potential for generating future returns, allowing for informed decision-making in investment opportunities.

Let’s have a more in depth look at the metrics (criterion) used:

Fundraising Totals Over the Last 5 Years. This metric provides insight into each firm’s ability to attract capital from investors over an extended period, reflecting investor confidence and the firm’s fundraising track record.

Total Private Equity AUM (in 2023). Total AUM for the private equity segment in 2023 serves as a measure of the firm’s scale and market presence within the private equity industry.

Private Equity Portfolio Returns (gross returns 2023). This metric represents the firm’s performance in generating returns from its investments in corporate private equity, providing a measure of investment effectiveness and value creation.

For each criterion, we will assign ranks to each firm based on their performance relative to others, with 1 being the highest rank and 5 being the lowest. We will then calculate the average score for each company and rank them accordingly. Each criterion weights the same.

Blackstone

Logo of Blackstone.
Logo of Blackstone
Source: the company.

Fundraising Totals: 126bn$

AUM: 304bn$

Gross returns: 12.1%

KKR

Logo of KKR.
Logo of KKR
Source: the company.

Fundraising Totals: 104bn$

AUM: 176bn$

Gross returns: 16%

The Carlyle Group (CG)

Logo of the Carlyle.
Logo of Carlyle
Source: the company.

Fundraising Totals: 70bn$

AUM: 161bn$

Gross returns: 5%

Apollo Global Management.

Logo of Apollo Global Management.
Logo of Apollo
Source: the company.

Fundraising Totals: 23bn$

AUM: 75.9bn$

Gross returns: 10.2%

TPG

Logo of TPG.
Logo of TPG
Source: the company.

Fundraising Totals: 55bn$

AUM: 97.8bn$

Gross returns: 14.1%

Conclusion

Once we consider all these elements, here are the ranks we obtain for each criterion and their average for each firm:

Therefore, our final ranking for the top 5 Private Equity firms globally in 2023 is:

  1. Blackstone
  2. KKR
  3. TPG
  4. The Carlyle Group
  5. Apollo Global Management

Note: Blackstone is ranked first in more criteria/metrics compared to KKR, demonstrating superior performance across multiple dimensions, and affirming its position as the top-performing firm in the final ranking.

Why should I be interested in this post?

As an ESSEC student enrolled in the SimTrade course, delving into the realm of Private Equity could be of great interest to you. This post serves as an insightful exploration into the industry’s key players, offering valuable insights into their distinctive characteristics. It presents an opportunity to deepen your understanding of the sector and potentially discover your future employer among these influential firms.

Related posts on the SimTrade blog

   ▶ Chloé ANIFRANI Top 5 Asset Management firms in Europe

   ▶ Lilian BALLOISDiscovering Private Equity: Behind the Scenes of Fund Strategies

Useful resources

Private Equity International

Forbes Top 10 U.S. Private Equity Firms Of March 2024

TPG Inc.

The Carlyle Group Inc.

KKR & Co Inc.

Apollo Global Management, Inc.

Blackstone Inc.

About the author

The article was written in March 2024 by Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023).

Posted in Contributors, Financial news | Leave a comment

My professional experience as a financial and accounting assistant at Professional Services

My professional experience as a financial and accounting assistant at Professional Services

Alessandro MARRAS

In this article, Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023) shares his professional experience as a financial and accounting assistant at Professional Services.

About the company

Professional Services was founded in 1986 by a team of professionals (lawyers, chartered accountants, and labor consultants), with the aim of providing services to businesses in the accounting, labor, administrative, tax, and corporate sectors. The mission is to offer entrepreneurs an integrated package of services capable of stimulating organizational transformations and facilitating the achievement of adequate levels of competitiveness. The target audience addressed by the Group primarily consists of Italian and foreign companies operating in the service sector and tertiary industries in general, as well as industrial, commercial, transportation, etc. With over thirty years of experience in the sector and an average annual group turnover of approximately €2,000,000, Professional Services can guarantee their clients the highest level of professionalism.

Logo of Professional Services.
Logo of Professional Services
Source: Professional Services.

As an assistant, I was part of the financial and accounting advisory department of Professional Services. In this department we were entrusted with critical responsibilities spanning the processing of accounting data and the provision of essential accounting and administrative services. The department served as the backbone of the organization, providing essential support across a spectrum of financial activities. We were responsible for maintaining accurate and up-to-date accounting records, ensuring the integrity of financial information. Moreover, we undertook the crucial task of preparing and analyzing financial statements, offering insights vital for informed decision-making. Additionally, the team managed various accounting and administrative services, including the maintenance of corporate books, providing corporate assistance, and overseeing the intricate landscape of taxation, encompassing value-added tax (VAT), personal income tax, corporate income tax, and regional tax on productive activities.

My internship

I had a 3-month internship at Professional Services as a financial and accounting assistant in 2023.

My missions

Over the course of these three months, my mission was to prepare and analyze the financial statements for our clients. I ensured that these statements were accurate and complied with relevant accounting standards, providing reliable insights for decision-making. This involved meticulously reviewing balance sheets, income statements, and cash flow statements for the given clients and reporting how these statements were in comparison to industry benchmarks. Moreover, I contributed to the maintenance of clients’ accounting records, assisting in the establishment of a comprehensive and organized financial record-keeping system. I did this through a software called Profis which helped by facilitating the compilation of balance sheets and declarations and performing tax simulations. Additionally, I handled various tasks related to invoicing, ensuring accurate processing and organization to facilitate smooth financial transactions for our clients. By fulfilling these responsibilities diligently, I aimed to support our clients in maintaining financial integrity, facilitating informed business decisions, and providing excellent service overall.

Required skills and knowledge

During this internship, I sharpened a combination of soft and hard skills that were indispensable for my position. Soft skills, such as effective communication, were essential. The ability to convey complex financial information clearly and succinctly to colleagues was crucial. Additionally, strong interpersonal skills facilitated collaboration within the team and ensured smooth workflow.

Attention to detail emerged as a critical soft skill, particularly when working with financial data and reports. The ability to meticulously analyze information and identify discrepancies was crucial for maintaining accuracy and reliability. Furthermore, time management skills were invaluable, as I often juggled various tasks and deadlines while prioritizing workload effectively.

On the hard skills front, proficiency in accounting principles and practices was fundamental. This included a thorough understanding of IFRS accounting regulations and principles, coupled with experience in financial statement preparation and analysis. Additionally, familiarity in applications such as a spreadsheet like Excel and an accounting software like Profis was essential. Mastery of Excel allowed me to manipulate and analyze financial data efficiently, while knowhow in Profis facilitated specific accounting operations and analyses required for the firm’s services.

Adaptability was also key, given the dynamic nature of the internship environment. The ability to quickly learn and adapt to new software and procedures ensured that I could contribute effectively to the team’s objectives. Overall, the combination of soft and hard skills enabled me to excel in my internship at Professional Services, providing me with invaluable experience and preparing me for future challenges in the field of finance and accounting.

What I learned

In terms of knowledge, I learned a multitude of valuable lessons that have significantly contributed to my professional growth and development. Firstly, I gained hands-on experience in financial statement preparation and analysis, improving my skills in interpreting financial data and drawing meaningful insights to support decision-making processes. Through my work. An integral part of this experience was learning to meticulously review and reconcile accounts to ensure accuracy in financial reporting. By identifying and correcting discrepancies between the general ledger and subsidiary accounts, I helped maintain the integrity of financial statements. Additionally, I deepened my understanding of IFRS (International Financial Reporting Standards) accounting principles and regulations, which are crucial for ensuring transparency, accountability, and comparability of financial statements. By familiarizing myself with these principles, I was able to assist in preparing financial statements that met regulatory requirements, enhancing the credibility and reliability of our clients’ financial information.

Moreover, working with software applications such as Excel and Profis expanded my technical proficiency, allowing me to efficiently manipulate and analyze financial data. This experience has enhanced my ability to leverage technology to streamline processes and improve productivity in the workplace.

On a broader level, my internship at Professional Services provided me with invaluable exposure to the dynamics of the finance and accounting industry, in the sense that I gained insight into the day-to-day operations of a consultancy firm, including client interactions, and the importance of maintaining accuracy and integrity in financial reporting.

Furthermore, collaborating with colleagues from diverse backgrounds, such as with different experiences, educational backgrounds and different areas of expertise, has improved my communication and teamwork skills, fostering an appreciation for the importance of effective collaboration in achieving organizational goals.

Overall, my internship experience at Professional Services has equipped me with a comprehensive skill set, valuable insights, and a deeper understanding of the finance and accounting profession, laying a strong foundation for my future career aspirations.

Financial concepts related my internship

Financial Statement Analysis

Financial statement analysis involves evaluating a company’s financial performance and position by examining its income statement, balance sheet, and cash flow statement. In my role, I actively participated in the preparation and analysis of financial statements for clients, ensuring accuracy and compliance with accounting standards.

Financial Reporting Standards

Financial reporting standards refer to a set of guidelines and rules established by regulatory bodies or standard-setting organizations to govern the preparation and presentation of financial statements. These standards aim to ensure consistency, transparency, and comparability in financial reporting across different organizations and industries. In my role, I applied financial reporting standards to prepare and review clients’ financial statements and records, ensuring accuracy and transparency in reporting.

Taxation

Taxation includes corporate income tax, applied to business profits, and value-added tax (VAT), imposed on goods and services at each stage of production. Corporate income tax understanding involves knowledge of tax laws, deductions, and applicable rates. Similarly, understanding VAT requires knowledge of registration, taxable transactions, and applicable rates. Even though I was not directly involved, the team was responsible in accounting for VAT and corporate income tax for clients, ensuring compliance with relevant regulations.

Why should I be interested in this post?

An ESSEC student aspiring to pursue a career in finance would find my experience at Professional Services particularly compelling. By sharing my experience as a financial and accounting assistant, I aim to offer fellow ESSEC students a glimpse into the practical application of finance concepts in a professional setting, inspiring and informing their own career aspirations in the field.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Louis DETALLE A quick review of the Audit job…

Useful resources

Professional Services

About the author

The article was written in March 2024 by Alessandro MARRAS (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange Semester, September 2023-December 2023).

Posted in Contributors, Professional experiences | Leave a comment

Tether: Unraveling the Impact of the Stablecoin on Modern Finance

 Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the cryptocurrency Tether.

Historical context and background

Tether (USDT) emerged in July 2014 as a groundbreaking cryptocurrency designed to bridge the gap between traditional fiat currencies and the digital realm. Conceived by Brock Pierce, Craig Sellars, and Reeve Collins, Tether aimed to offer a stable alternative to the price volatility commonly associated with other cryptocurrencies like Bitcoin. Functioning as a stablecoin, Tether is pegged to the value of a fiat currency, primarily the US Dollar, maintaining a 1:1 ratio. This pegging mechanism provides a degree of price stability, making Tether an attractive option for traders and investors seeking to mitigate the risks inherent in the crypto market. Since its inception, Tether has grown to become one of the most widely used cryptocurrencies, playing a pivotal role in facilitating liquidity and serving as a gateway for funds within the broader digital asset ecosystem. Despite its popularity, Tether has faced scrutiny regarding its transparency and reserve backing, adding layers of complexity to its intriguing history within the crypto landscape.

Tether Logo

Source: Yahoo! Finance

Figure 1. Key Dates in Tether History

Source: Yahoo! Finance

Key features

  • Stability: Tether is designed to maintain a 1:1 peg with a fiat currency, typically the US Dollar. This pegging mechanism provides stability in value, reducing the volatility commonly associated with other cryptocurrencies.
  • Widespread Adoption: Tether is widely adopted across various cryptocurrency exchanges and platforms. Its broad acceptance makes it a popular choice for traders and investors.
  • Liquidity Provider: Tether serves as a crucial source of liquidity within the cryptocurrency market. Traders often use USDT as a safe haven during times of market turbulence.
  • Fast Transactions: Tether transactions are conducted on blockchain networks like Ethereum and Tron, enabling fast and efficient cross-border transactions compared to traditional banking systems.
  • Global Accessibility: Tether provides a borderless financial solution, allowing users to send and receive funds globally without the need for traditional banking intermediaries.
  • Smart Contract Compatibility: Tether is compatible with blockchain-based smart contracts, enabling developers to integrate it into decentralized applications (DApps) for various financial services.

Use cases

  • Trading Pairs: Tether is extensively used as a trading pair on cryptocurrency exchanges. It allows traders to quickly move in and out of positions while avoiding the market volatility associated with other digital assets.
  • Hedging: Investors often use Tether as a hedging tool to safeguard their portfolios against market fluctuations. By converting their holdings to USDT during uncertain times, investors can protect their capital.
  • Remittances: Tether facilitates cross-border remittances, offering a faster and potentially more cost-effective alternative to traditional money transfer services.
  • Stable Value Storage: Tether serves as a stable store of value, allowing users to preserve their wealth in a cryptocurrency that is less prone to price fluctuations compared to other volatile digital assets.
  • Decentralized Finance (DeFi): Tether is a common stablecoin used in decentralized finance protocols for lending, borrowing, and yield farming activities within the growing DeFi ecosystem.
  • Tokenized Assets: Tether is utilized to represent traditional assets in tokenized form on blockchain platforms, enabling fractional ownership and increased liquidity for real-world assets.

Controversy

While Tether has gained popularity for its stability and utility, it has also faced criticism and regulatory scrutiny, particularly regarding its reserve backing and transparency. The paper “Is Bitcoin Really Untethered?”, analyses Tether’s controversies revealing that the significant growth of Tether, the largest pegged cryptocurrency, may not solely be driven by organic investor demand but also by a scheme to artificially inflate cryptocurrency prices. By analyzing the blockchains of Bitcoin and Tether, the researchers found evidence suggesting that a major player on Bitfinex utilizes Tether to purchase large amounts of Bitcoin during price downturns, effectively supporting Bitcoin prices. This intervention is particularly pronounced near round-number price thresholds, indicating a strategic approach to price support. The data also suggests that Tether issuance correlates with a month-end need for dollar reserves, implying partial reserve backing. Overall, these findings lend support to the hypothesis that Tether’s growth is supply-driven and potentially manipulative.

Furthermore, the paper highlights the broader implications of these findings, suggesting that price manipulation in cryptocurrencies can have significant distortive effects beyond standard supply-and-demand dynamics. It highlights the need for external surveillance, monitoring, and regulatory frameworks in the cryptocurrency space, challenging the notion that innovative technologies alone can bypass the need for traditional oversight. The conclusion suggests that while cryptocurrencies offer new possibilities for financial innovation, they are not immune to the risks associated with dubious activities and speculative bubbles, which could ultimately lead to further price distortions and negative impacts on the market.

Technology and underlying blockchain

Tether (USDT), a the stablecoin, utilizes blockchain technology across various networks to provide a digital asset pegged to traditional fiat currencies. The Ethereum-based ERC-20 version is the most prevalent, benefiting from Ethereum’s widespread adoption and smart contract capabilities, making it a cornerstone for decentralized exchanges and DeFi applications. Tether also operates on the Tron blockchain (TRC-20), offering faster transactions and reduced fees, particularly appealing for high-frequency trading. Acknowledging the demand for scalability and cost-effectiveness, Tether has expanded to alternative blockchains like Binance Smart Chain and Solana. These adaptations highlight Tether’s commitment to meeting diverse market needs. Managed by Tether Limited, the stablecoin asserts stability through regular audits and claims of holding equivalent fiat reserves, although controversies have arisen regarding transparency. The dynamic interplay of Tether across various blockchains underscores its pivotal role in the evolving landscape of digital finance.

Supply of coins

The market supply of Tether (USDT), a leading stablecoin, plays a crucial role in the broader cryptocurrency ecosystem. Tether’s supply dynamics are intrinsically linked to its unique issuance mechanism. Tether Limited, the company behind USDT, mints new tokens by receiving equivalent amounts of fiat currency, primarily the US Dollar, in its reserves. This issuance process is supposed to ensure a 1:1 peg between USDT and the underlying fiat currency, promoting price stability.

The market supply of Tether expands as demand for the stablecoin increases. Traders and investors often turn to USDT as a safe haven during times of high volatility, effectively increasing the circulating supply. This heightened demand results in additional Tether being issued to maintain the peg, thus influencing the overall supply in the market.

Monitoring Tether’s supply is of particular interest due to its significant impact on liquidity within the cryptocurrency space. An influx of USDT into the market provides traders with a reliable means to navigate price fluctuations without fully exiting the crypto market, enhancing liquidity and potentially mitigating market volatility.

Historical data for Tether

How to get the data?

The Tether is popular cryptocurrency on the market, and historical data for the Tether such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for Tether on Yahoo! Finance (the Yahoo! code for Tether is USDT-USD).

Figure 1. Tether data

Source: Yahoo! Finance.

Historical data for the Tether market prices

Exploring the historical market price of Tether (USDT) unveils a wealth of insights into the cryptocurrency’s role and its impact on the broader market. The stability of Tether, designed to maintain a 1:1 peg with traditional fiat currencies, is reflected in its price history. Observing deviations from this peg over time provides a gauge of Tether’s effectiveness as a stablecoin. Moreover, fluctuations in Tether’s historical price serve as a barometer for market sentiment, indicating periods of increased demand for stability during cryptocurrency market volatility. Tether’s price movements also offer a lens into liquidity trends, showcasing its role in various financial activities within the crypto ecosystem. Crucially, analyzing Tether’s historical price can illuminate market responses to controversies, regulatory developments, and its correlation with other major cryptocurrencies. Understanding these dynamics is essential for investors and traders seeking to navigate the intricate landscape of digital assets and stablecoins.

Figure 2 below represents the evolution of the price of Tether in US dollar over the period Nov 2017 – Dec 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 2. Evolution of the Tether price

Source: Yahoo! Finance.

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the Ethereum.

Download R file

Data file

The R program that you can download above allows you to download the data for the Ethereum from the Yahoo! Finance website. The database starts on December, 2017.

Table 1 below represents the top of the data file for the Ethereum downloaded from the Yahoo! Finance website with the R program.

Table 1. Top of the data file for the Tether

Source: computation by the author (data: Yahoo! Finance website).

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Download the Excel file with Tether data

Python script to download Ethereum historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for Tether

eth_ticker = “USDT-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

usdt_data = yf.download(eth_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

usdt_df = pd.DataFrame(usdt_data)

# Define the Excel file path

excel_file_path = “tether_historical_data.xlsx”

# Save the data to an Excel sheet

usdt_df.to_excel(excel_file_path, sheet_name=”USDT Historical Data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the Tether

Figure 3 below gives the evolution of the Tether on a daily basis.

Figure 3. Evolution of the Tether.

Source: computation by the author (data: Yahoo! Finance website).

Figure 4 below gives the evolution of the Tether returns from November 09, 2017 to December 31, 2022 on a daily basis.

Figure 4. Evolution of the Tether returns.

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Ethereum

The R program that you can download above also allows you to compute summary statistics about the returns of the Tether.

Table 4 below presents the following summary statistics estimated for the Ethereum:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 2. Summary statistics for Tether.

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Tether returns

Historical distribution

Figure 5 represents the historical distribution of the Tether daily returns for the period from November 09, 2017 to December 31, 2022.

Figure 5. Historical Tether distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from November 09, 2017 to December 31, 2022.

Figure 6 below represents the Gaussian distribution of the Tether daily returns with parameters estimated over the period from November 09, 2017 to December 31, 2022.

Figure 6. Gaussian distribution of the Tether returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Tether returns

The R program that you can download above also allows you to compute risk measures about the returns of the tether.

Table 3 below presents the following risk measures estimated for the Ethereum:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the Tether.

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the XRP while the study of the right tail is relevant for an investor holding a short position in the XRP.

Why should I be interested in this post?

Tether is a compelling subject for students, especially those in finance, economics, business, and technology. Ripple’s focus on revolutionizing cross-border transactions and its unique blockchain technology offer insights into innovations in financial technology. Exploring Tether provides a deeper understanding of blockchain, cryptocurrency markets, stable coins, regulatory challenges, and the practical applications of decentralized systems. Students can gain valuable knowledge about market dynamics, investment opportunities, and the intersection of technology and finance by delving into the complexities of Tether and its impact on the financial industry.

Related posts on the SimTrade blog

About cryptocurrencies

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

   ▶ Snehasish CHINARA How to get crypto data

   ▶ Alexandre VERLET Cryptocurrencies

   ▶ Youssef EL QAMCAOUIDecentralised Financing

   ▶ Hugo MEYERThe regulation of cryptocurrencies: what are we talking about?

   ▶ JOHN M. GRIFFIN, AMIN SHAMS Is Bitcoin Really Untethered?

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

   ▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for Tether

CoinMarketCap Historical data for Tether

About the author

The article was written in January 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Posted in Contributors | Tagged , , , | Leave a comment

XRP: Pioneering Financial Revolution

 Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024) explains the cryptocurrency XRP/Ripple.

Historical context and background

XRP, the digital currency associated with the Ripple network, emerged against the backdrop of a growing interest in blockchain technology and its potential applications beyond cryptocurrencies. The development of Ripple began in 2012 when Jed McCaleb, Chris Larsen, and Arthur Britto joined forces to create a decentralized digital currency system. Ripple Labs, the company behind XRP, aimed to address the inefficiencies in traditional cross-border payments by providing a fast and cost-effective alternative. Unlike Bitcoin, which relies on a proof-of-work consensus mechanism, Ripple utilizes a unique consensus algorithm called the Ripple Protocol Consensus Algorithm (RPCA). The XRP Ledger, the underlying technology, is designed to facilitate quick and secure transactions, making it particularly appealing for financial institutions. Over the years, Ripple has garnered both support and criticism within the crypto community due to its centralized nature and ongoing legal challenges. Nevertheless, its focus on facilitating seamless global transactions has positioned XRP as a significant player in the evolving landscape of digital assets.

XRP Logo

Source: Yahoo! Finance

Figure 1. Key Dates in XRP History

Source: Yahoo! Finance and other internet sources

Key features and use cases

  • Fast and Low-Cost Transactions: One of the primary features of XRP is its speed and cost-effectiveness. The XRP Ledger is capable of processing transactions in just a few seconds, making it significantly faster than traditional banking systems and some other cryptocurrencies. The low transaction fees associated with XRP contribute to its appeal for cross-border payments.
  • Liquidity and Scalability: XRP is designed to handle a high volume of transactions, providing liquidity for financial institutions. This scalability is crucial for the adoption of XRP in large-scale financial applications, including remittances and institutional transfers.
  • Interoperability: Ripple aims to facilitate interoperability between different financial systems. XRP can act as a bridge currency between fiat currencies, enabling seamless and efficient transactions across borders. This interoperability is particularly valuable in the context of global finance.
  • Decentralization with Unique Consensus Algorithm: While Ripple has faced criticism for some aspects of centralization, the XRP Ledger employs the Ripple Protocol Consensus Algorithm (RPCA) for transaction validation. This consensus mechanism is more energy-efficient compared to proof-of-work used by some other cryptocurrencies.
  • Partnerships with Financial Institutions: Ripple has formed partnerships with various financial institutions, including banks and payment service providers. The aim is to leverage XRP for real-time, cross-border payments, reducing settlement times and costs for these institutions.
  • Smart Contracts and Tokenization: Ripple has also explored adding smart contract functionality to the XRP Ledger, expanding its use cases beyond simple transactions. Additionally, the platform has the potential for tokenization of real-world assets, allowing for the representation of various assets on the blockchain.
  • Stability and Predictable Supply: XRP has a fixed supply of 100 billion tokens, with a portion held by Ripple Labs. This fixed supply aims to provide stability and predictability, which could be attractive for businesses and investors.

While XRP has faced regulatory challenges and debates about its decentralization, its unique features and focus on solving real-world financial issues position it as a cryptocurrency with substantial potential in the global financial landscape.

Technology and underlying blockchain

XRP, the cryptocurrency associated with the Ripple network, operates on a distinct technological framework, utilizing a consensus algorithm that sets it apart from traditional proof-of-work systems. At the heart of XRP’s technology is the XRP Ledger, a decentralized blockchain that enables fast and secure transactions. The unique consensus mechanism employed by Ripple is known as the Ripple Protocol Consensus Algorithm (RPCA). Unlike the energy-intensive mining processes seen in proof-of-work systems, RPCA operates on a consensus model that involves a network of independent validators reaching agreement on the order and validity of transactions. This consensus mechanism allows the XRP Ledger to achieve high throughput and swift confirmation times, making it well-suited for the efficient processing of cross-border payments and financial transactions. Additionally, the XRP Ledger supports the issuance of various tokens, potentially expanding its use cases beyond its native cryptocurrency. Despite debates about the decentralization of Ripple, the technology behind XRP continues to evolve, showcasing a commitment to addressing the challenges and opportunities in the rapidly evolving blockchain and cryptocurrency space. Additionally, the platform has explored the integration of smart contract functionality, opening possibilities for more complex and programmable transactions. The focus on scalability, interoperability, and speed positions XRP as a blockchain solution tailored for the demands of the global financial industry, particularly in the context of cross-border payments and remittances.

Supply of coins

The supply dynamics of XRP, the native cryptocurrency of the Ripple network, play a crucial role in shaping its market characteristics. Unlike Bitcoin, which relies on a mining process to gradually release new coins into circulation, XRP was created with its entire supply generated at inception. XRP has a fixed maximum supply of 100 billion coins, a feature that distinguishes it from some other cryptocurrencies with potentially infinite supplies. Notably, a substantial portion of the XRP supply is held by Ripple Labs, the company behind the cryptocurrency. Approximately 55 billion XRP are held in escrow by Ripple Labs, the company behind the development of the Ripple protocol. This escrow mechanism is designed to release a specific amount of XRP into circulation each month, reducing the potential for market manipulation and ensuring a predictable supply trajectory.

This allocation has been a point of discussion and scrutiny within the crypto community, with debates surrounding the potential impact of such centralization on the coin’s decentralization ethos. Ripple has taken steps to address concerns, implementing strategies such as the escrow system, which locks a large amount of XRP in time-released contracts to be gradually released into circulation. The controlled release aims to provide transparency and mitigate concerns related to sudden market influxes. The fixed supply, along with Ripple’s strategic initiatives, contributes to the stability and predictability of XRP in the market, influencing investor perceptions and shaping the overall market dynamics of the cryptocurrency.

Figure 2. Number of XRP Transaction per Day

Source: BitInfoCharts (Ethereum Transactions historical chart)

Historical data for XRP

How to get the data?

The XRP is popular cryptocurrency on the market, and historical data for the XRP such as prices and volume traded can be easily downloaded from the internet sources such as Yahoo! Finance, Blockchain.com & CoinMarketCap. For example, you can download data for XRP on Yahoo! Finance (the Yahoo! code for XRP is XRP-USD).

Figure 3. XRP data

Source: Yahoo! Finance

Historical data for the XRP market prices

Access to historical data on XRP, the cryptocurrency affiliated with Ripple, offers investors valuable insights and tools for decision-making. By analyzing past price trends and patterns, investors can better anticipate potential movements in XRP’s value, aiding in strategic buy or sell decisions. Historical data also serves as a record of XRP’s volatility, allowing investors to assess and manage risks effectively. Examining market sentiment during different periods provides a nuanced understanding of external factors that may impact XRP, such as regulatory developments or technological upgrades. Additionally, historical performance comparisons with other cryptocurrencies or traditional assets help investors evaluate XRP’s relative strength and potential for returns, informing optimal portfolio management. Event analysis around significant occurrences, such as partnerships or regulatory changes, assists in anticipating market reactions to future events. Furthermore, historical data aids in identifying market cycles, supporting investors in aligning their strategies with the prevailing market conditions. Recognizing key support and resistance levels based on historical prices enhances risk management by guiding entry and exit points. While historical data is a valuable tool, investors should blend it with current market analysis and fundamental factors for comprehensive decision-making, considering the inherent unpredictability of the cryptocurrency market.

Figure 4 below represents the evolution of the price of XRP in US dollar over the period Nov 2017 – Dec 2023. The price corresponds to the “closing” price (observed at 10:00 PM CET at the end of the month).

Figure 4. Evolution of the XRP price

Source: Yahoo! Finance

R program

The R program below written by Shengyu ZHENG allows you to download the data from Yahoo! Finance website and to compute summary statistics and risk measures about the XRP.

Download R file

Data file

The R program that you can download above allows you to download the data for the Ethereum from the Yahoo! Finance website. The database starts on December, 2017.

Table 3 below represents the top of the data file for the Ethereum downloaded from the Yahoo! Finance website with the R program.

Table 3. Top of the data file for XRP.

Source: computation by the author (data: Yahoo! Finance website)

Python code

You can download the Python code used to download the data from Yahoo! Finance.

Download the Excel file with Ethereum data

Python script to download XRP historical data and save it to an Excel sheet::

import yfinance as yf

import pandas as pd

# Define the ticker symbol for Ethereum

xrp_ticker = “XRP-USD”

# Define the date range for historical data

start_date = “2020-01-01”

end_date = “2022-01-01”

# Download historical data using yfinance

xrp_data = yf.download(xrp_ticker, start=start_date, end=end_date)

# Create a Pandas DataFrame from the downloaded data

xrp_df = pd.DataFrame(xrp_data)

# Define the Excel file path

excel_file_path = “xrp_historical_data.xlsx”

# Save the data to an Excel sheet

xrp_df.to_excel(excel_file_path, sheet_name=”XRP Historical Data”)

print(f”Data saved to {excel_file_path}”)

# Make sure you have the required libraries installed and adjust the “start_date” and “end_date” variables to the desired date range for the historical data you want to download.

Evolution of the Ethereum

Figure 5 below gives the evolution of the Ethereum on a daily basis.

Figure 5. Evolution of the XRP.

Source: computation by the author (data: Yahoo! Finance website).

Figure 6 below gives the evolution of the Ethereum returns from November 09, 2017 to December 31, 2022 on a daily basis.

Figure 6. Evolution of the XRP returns.

Source: computation by the author (data: Yahoo! Finance website).

Summary statistics for the Ethereum

The R program that you can download above also allows you to compute summary statistics about the returns of the Ethereum.

Table 4 below presents the following summary statistics estimated for the Ethereum:

  • The mean
  • The standard deviation (the squared root of the variance)
  • The skewness
  • The kurtosis.

The mean, the standard deviation / variance, the skewness, and the kurtosis refer to the first, second, third and fourth moments of statistical distribution of returns respectively.

Table 4. Summary statistics for XRP

Source: computation by the author (data: Yahoo! Finance website).

Statistical distribution of the Ethereum returns

Figure 7 represents the historical distribution of the Ethereum daily returns for the period from November 09, 2017 to December 31, 2022.

Figure 7. Historical XRP distribution of the returns.

Source: computation by the author (data: Yahoo! Finance website).

Gaussian distribution

The Gaussian distribution (also called the normal distribution) is a parametric distribution with two parameters: the mean and the standard deviation of returns. We estimated these two parameters over the period from November 09, 2017 to December 31, 2022.

Figure 8 below represents the Gaussian distribution of the XRP daily returns with parameters estimated over the period from November 09, 2017 to December 31, 2022.

Figure 9. Gaussian distribution of the XRP returns.

Source: computation by the author (data: Yahoo! Finance website).

Risk measures of the Ethereum returns

The R program that you can download above also allows you to compute risk measures about the returns of the Ethereum.

Table 5 below presents the following risk measures estimated for the Ethereum:

  • The long-term volatility (the unconditional standard deviation estimated over the entire period)
  • The short-term volatility (the standard deviation estimated over the last three months)
  • The Value at Risk (VaR) for the left tail (the 5% quantile of the historical distribution)
  • The Value at Risk (VaR) for the right tail (the 95% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the left tail (the average loss over the 5% quantile of the historical distribution)
  • The Expected Shortfall (ES) for the right tail (the average loss over the 95% quantile of the historical distribution)
  • The Stress Value (SV) for the left tail (the 1% quantile of the tail distribution estimated with a Generalized Pareto distribution)
  • The Stress Value (SV) for the right tail (the 99% quantile of the tail distribution estimated with a Generalized Pareto distribution)

Table 5. Risk measures for the XRP.

Source: computation by the author (data: Yahoo! Finance website).

The volatility is a global measure of risk as it considers all the returns. The Value at Risk (VaR), Expected Shortfall (ES) and Stress Value (SV) are local measures of risk as they focus on the tails of the distribution. The study of the left tail is relevant for an investor holding a long position in the XRP while the study of the right tail is relevant for an investor holding a short position in the XRP.

Why should I be interested in this post?

XRP, the cryptocurrency associated with Ripple, is a compelling subject for students, especially those in finance, economics, business, and technology. Ripple’s focus on revolutionizing cross-border transactions and its unique blockchain technology offer insights into innovations in financial technology. Exploring XRP provides a deeper understanding of blockchain, cryptocurrency markets, regulatory challenges, and the practical applications of decentralized systems. Students can gain valuable knowledge about market dynamics, investment opportunities, and the intersection of technology and finance by delving into the complexities of XRP and its impact on the financial industry.

Related posts on the SimTrade blog

About cryptocurrencies

   ▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

   ▶ Snehasish CHINARA How to get crypto data

   ▶ Alexandre VERLET Cryptocurrencies

   ▶ Youssef EL QAMCAOUIDecentralised Financing

   ▶ Hugo MEYERThe regulation of cryptocurrencies: what are we talking about?

About statistics

   ▶ Shengyu ZHENG Moments de la distribution

   ▶ Shengyu ZHENG Mesures de risques

   ▶ Jayati WALIA Returns

Useful resources

Academic research about risk

Longin F. (2000) From VaR to stress testing: the extreme value approach Journal of Banking and Finance, N°24, pp 1097-1130.

Longin F. (2016) Extreme events in finance: a handbook of extreme value theory and its applications Wiley Editions.

Data

Yahoo! Finance

Yahoo! Finance Historical data for XRP

CoinMarketCap Historical data for XRP

About the author

The article was written in January 2024 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2024).

Posted in Contributors | Tagged , , , | Leave a comment

Unifying Forces: Cross-Border AML Collaboration in Safeguarding Global Finances

Unifying Forces: Cross-Border AML Collaboration in Safeguarding Global Finances

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) presents the cross-border collaboration of national entities to prevent money laundering.

Introduction

In an era marked by unprecedented global connectivity, the fight against financial crimes, particularly money laundering, has transcended national boundaries. The escalating sophistication of financial crimes, coupled with the interconnectedness of the global economy, has underscored the need for collaborative approaches to tackle money laundering.

Cross-border anti-money laundering (AML) collaboration involves the sharing of intelligence, resources, and best practices among nations, regulatory authorities, and financial institutions to effectively thwart illicit financial activities that transcend borders.

Money laundering rarely respects national borders. Criminal organizations exploit gaps in regulatory frameworks, leveraging multiple jurisdictions to obscure the origins of illicit funds. Cross-border collaboration is essential to address this globalized nature of financial crimes.

According to UNODC (United Nations Office on Drugs and Crime), the estimated amount of money laundered globally in one year is between 2 to 5% of global GDP, or between $800 billion to $2 trillion in current US dollars. Due to the clandestine nature of money-laundering, it is however difficult to estimate the total amount of money that goes through the laundering cycle.

Key Elements of Cross-Border AML Collaboration

Information Sharing

Collaborative platforms used by national entities enable countries to share vital information about suspicious transactions, emerging trends, and high-risk entities. Timely information exchange enhances the ability to detect and prevent money laundering activities.

Standardization of AML Practices

Establishing common standards for AML practices ensures consistency across borders. Harmonizing regulations and procedures facilitates smoother collaboration, reduces regulatory arbitrage, and creates a united front against money laundering.

For example, in cryptocurrency, the Travel Rule mandates global sharing of customer information during transactions, aligning with guidelines of the Financial Action Task Force on Money Laundering (FATF) for standardized anti-money laundering practices. This ensures consistency and strengthens defenses against illicit financial activities.

Mutual Legal Assistance Treaties

A Mutual Legal Assistance Treaty (MLAT) provides a legal framework for countries to request and provide assistance in legal matters, including the investigation and prosecution of money laundering. Strengthening and expanding these treaties contribute to more effective cross-border collaboration.

For instance, if Country A is investigating financial crimes and requires bank records from Country B, both nations, bound by an MLAT, can exchange information, and collaborate on the investigation, enhancing the effectiveness of their legal systems in combating transnational crimes.

Technological Integration

Leveraging technology, such as advanced analytics and artificial intelligence, facilitates the identification of patterns indicative of money laundering. Shared technological solutions enhance the efficiency of AML efforts across borders.

Joint Investigations

Cross-border collaboration allows for joint investigations involving law enforcement agencies from multiple countries. This coordinated approach increases the chances of uncovering complex money laundering schemes and holding perpetrators accountable.

Role of FATF in Cross-Border AML Collaboration?

Established in 1989, the Financial Action Task Force on Money Laundering (FATF) is a professional association comprising member countries and jurisdictions committed to combating money laundering and terrorist financing. This intergovernmental organization sets international standards, develops policies, and conducts assessments to promote effective Anti-Money Laundering (AML) and Counter-Terrorist Financing (CTF) measures worldwide.

Key Contributions of FATF in Cross-Border AML:

  • Setting International Standards: FATF establishes and updates a set of AML and CTF standards, commonly known as the FATF Recommendations. These standards provide a unified foundation for countries to strengthen their legal, regulatory, and operational frameworks against money laundering and terrorist financing.
  • Mutual Evaluations: FATF conducts regular mutual evaluations, wherein member countries assess each other’s compliance with FATF Recommendations. This process fosters transparency and accountability, encouraging nations to enhance their AML and CTF efforts.
  • Issuing Public Statements: When a country is identified as having deficiencies in its AML/CTF framework, FATF issues public statements, creating international awareness. This mechanism encourages corrective actions and bolsters cross-border cooperation to address vulnerabilities.
  • International Cooperation and Information Sharing: This collective effort strengthens the ability to identify and combat transnational financial crimes.

Benefits and Challenges

As technology continues to advance, collaborative efforts are poised to become more sophisticated, providing an even greater advantage in the ongoing battle against money laundering. Cross-border AML collaboration offers numerous benefits, including enhanced detection capabilities, stronger deterrence against financial crimes, and the establishment of a more resilient global financial system.

Though there are several benefits for the cross-border AML collaboration, it is also quite challenging to find good solutions.

Differing Legal Frameworks

Varied legal frameworks across countries pose challenges. Establishing common principles and encouraging mutual recognition of legal systems can help address disparities.

Cultural and Language Barriers

Cultural and language differences can impede effective collaboration. Training programs and cultural awareness initiatives foster better communication and understanding among collaborating entities.

Data Privacy Concerns

Data privacy regulations can hinder information sharing. Implementing robust data protection measures and ensuring compliance with privacy laws are crucial for overcoming this challenge.

Why should I be interested in this post?

If you decide to work in the realms of finance, international law, or even within a multinational corporation, understanding the intricacies of cross-border collaboration in Anti-Money Laundering (AML) becomes a must. This knowledge not only ensures regulatory compliance for businesses operating across borders but also provides professionals with insights into legal frameworks, treaties, and diplomatic efforts that underpin a secure and stable global financial landscape.

Related posts on the SimTrade blog

   ▶ Akshit GUPTA Market manipulation

   ▶ Louis DETALLE The 3 biggest corporate frauds of the 21st century

Useful resources

United Kingdom government Action plan for anti-money laundering and counter-terrorist finance

IMF Combating the finance of terrorism

Financial crimes enforcement network (US agency) History of anti-money laundering laws

Financial Action Task Force on Money Laundering (FATF)

Mutual Legal Assistance Treaties (with the US)

About the author

The article was written in March 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Posted in Contributors | Leave a comment

Market Consensus Based on Financial Analysts’ Forecasts

Market Consensus Based on Financial Analysts’ Forecasts

Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) explains what is the market consensus based on financial analysts’ forecasts.

Introduction

Market consensus represents the average derived from the individual predictions made by financial analysts who closely monitor and analyze corporate and market conditions. In the context of financial analysts’ forecasts, the consensus refers to the collective expectation or average prediction of a group of analysts regarding the future performance of a firm measured by sales and profits, of a financial asset such as a stock, commodity, or currency. Few examples of market consensus based on financial analysts forecast would be: Forecasts for economic indicators such as GDP growth, inflation rates, or unemployment levels. It is derived from the aggregated predictions of various analysts, providing a consensus viewpoint on the expected direction or magnitude of economic changes. Forecasts of the future exchange rates between currencies such as the euro/dollar rate. If multiple analysts predict the exchange rates for the Euro to U.S. Dollar, the market consensus would be an average or median of these forecasts, indicating the collective expectation for the currency pair. Forecasts of price targets for stocks based on the projections of future performance. If a market stock is covered by multiple analysts, the market consensus price target would be the average of those figures, giving investors a benchmark for assessing the stock’s anticipated value. Forecasts of the company’s earnings per share (EPS). The market consensus, in this case, would be the average or median of these individual EPS predictions, representing the collective expectation of analysts regarding Company’s earnings. Forecasts of commodity prices such as oil, gold, or agricultural products. The market consensus for a commodity’s future price is determined by averaging or considering the median of these individual forecasts, reflecting the consensus view on the commodity’s likely trajectory.

Key participants

Financial analysts

Talk about financial analysts: who are they?where do they work? To determine the market consensus for Apple Inc. (AAPL), one would typically aggregate and analyze the forecasts and estimates provided by sell-side financial analysts who cover the company. These analysts regularly publish their projections for key financial metrics such as revenue, earnings per share (EPS), and other performance indicators.

Market consensus firms

Market consensus firms specialize in producing market consensus based on financial analysts’ forecasts and opinions. These firms aggregate and analyze data from multiple analysts to provide a consensus view on various financial metrics such as earnings estimates, revenue projections, and target prices for individual stocks and broader market indices. Some prominent firms that offer market consensus based on financial analysts’ input include: FactSet: FactSet aggregates and standardizes data from various sources, including sell-side analysts, to provide consensus estimates for earnings, revenue, and other financial metrics. Their platform offers detailed consensus estimates for individual companies, sectors, and industries. Refinitiv (formerly Thomson Reuters): Refinitiv offers consensus estimates and forecasts compiled from sell-side analysts’ research reports. Their platform provides consensus data on earnings, revenue, and other key financial metrics for equities, fixed income, and commodities. IBES by Refinitiv: IBES (Institutional Brokers’ Estimate System) is a leading database of consensus estimates and analyst recommendations. It offers comprehensive coverage of earnings estimates, revenue projections, and other financial metrics for thousands of companies globally.

Data providers

Companies that provide financial data and analytics services play a crucial role. They compile and disseminate information about analysts’ forecasts, making it accessible to various participants in the financial ecosystem. Bloomberg is a prominent example here, its terminal, a widely used platform in the financial industry, aggregates and delivers a vast array of financial data, including analysts’ predictions and consensus estimates. It also exemplifies how data providers contribute to the transparency and accessibility of financial analysts’ forecasts.

Investors

Investors rely on the forecasts and predictions made by financial analysts to make informed investment decisions. The market consensus provides investors with a collective viewpoint, helping them assess potential risks and returns. Their role is pivotal in the financial markets, and they interact with market consensus in several ways like decision making, portfolio construction, risk assessment, performance evaluation, communication with shareholders, etc.

Traders

Traders are individuals or entities that actively buy and sell financial instruments, such as stocks, bonds, currencies, or commodities, with the aim of making short-term profits. Traders can be categorized into various types, including day traders, swing traders, and algorithmic traders, each with a different time horizon and approach to the market. There are various types of traders, each with different strategies, time horizons, and goals. Few examples of them would be day trader, swing trader, Algo trader, position trader, scalper, options trader, forex trader and commodity trader.

Process for building a market consensus

Building a market consensus involves aggregating the predictions and expectations of various financial analysts, experts, and stakeholders regarding the future performance of a financial instrument, economic indicator, or asset.

There are certain steps we typically follow in this process:

  • Data collection of forecasts: Financial analysts, often employed by brokerage firms, investment banks, or independent research firms, conduct in-depth analyses of specific assets, companies, or economic indicators. They generate individual forecasts based on factors such as earnings projections, economic data, and market trends.
  • Analyst Ratings and Recommendations: Analysts may assign ratings (e.g., buy, hold, sell) and provide recommendations for investors. These ratings and recommendations reflect their views on the expected performance of a particular asset. These assessments contribute to the overall market consensus.
  • Normalization: Before computing the consensus, the data may undergo normalization to ensure consistency across different analysts’ estimates. This step involves adjusting for any variations in reporting standards, accounting methods, or other factors that could affect the comparability of estimates.
  • Weighting: Some consensus providers may apply weighting to analysts’ estimates based on factors such as historical accuracy, reputation, or coverage universe. Weighting ensures that more accurate or influential analysts have a greater impact on the consensus.
  • Calculation: The market consensus is calculated by averaging the aggregated forecasts and estimates from all contributing analysts. This average represents the consensus view of analysts regarding the expected performance of the company or market index for the specified period.
  • Dissemination: The computed consensus estimates are then disseminated to clients through various channels, such as financial data platforms, research reports, and market data terminals. Clients use this information to assess market expectations, benchmark against their own forecasts, and make investment decisions.
  • Tracking and Updates: Market consensus providers continuously track and update the consensus estimates as new information becomes available. This includes incorporating revisions to analysts’ forecasts, earnings announcements, and other relevant developments that may impact the consensus view.

It’s important to note that while market consensus based on financial analysts’ estimates provides valuable insights into market expectations, it is not a guarantee of future performance. Investors should consider various factors, conduct their own analysis, and exercise judgment when making investment decisions. Additionally, consensus estimates are subject to revisions over time as new information emerges and analysts update their forecasts. The market consensus is key to understand how financial markets work, how stock market prices react to the announcements of profits by firms or economic indicators.

Quality of the market consensus

Behavioral Influences

Beyond numbers and charts, market consensus is deeply influenced by human behavior. Emotions, biases, and psychological factors play a significant role in shaping consensus views. Behavioral finance studies, backed by statistical evidence, highlight how psychological biases such as herding, overreaction, and anchoring contribute to the formation and evolution of consensus views.

Talk about Dot bubble of the 2000s

The late 1990s saw the widespread adoption of the internet for both commercial and personal use. In 2000, the stock market experienced a significant downturn. Dot-com stocks, in particular, faced sharp declines, wiping out substantial market capitalization. The Dot-Com Bubble refers to the rapid rise, speculative frenzy, and subsequent collapse of stock prices of many internet-based companies in the late 1990s and early 2000s.

Example: market consensus for Apple

The prevailing market sentiment toward Apple Inc. (AAPL) is generally optimistic, according to analyst assessments. As reported by Stock Analysis, the consensus among 32 analysts places the average price target for Apple’s stock at $203.25. The range spans from a low estimate of $120 to a high estimate of $250. Based on this average target, a potential increase of approximately 11.48% is anticipated from the current stock price of $182.32. Notably, analysts collectively advocate a “Buy” rating for Apple.

source: Yahoo website – https://finance.yahoo.com/quote/AAPL/analysis/

Yahoo Finance offers in-depth projections for Apple’s financial performance, encompassing estimates for earnings and revenue across upcoming quarters and years. For the ongoing quarter concluding in March 2024, analysts predict an average earnings per share (EPS) of $1.51, accompanied by revenue estimates averaging $91.02 billion. These forecasts align with a broader outlook suggesting a growth trajectory for Apple, with both EPS and revenue anticipated to expand in the subsequent years. For those seeking more comprehensive analyses and real-time updates on Apple’s stock performance, as well as expert opinions from analysts, a direct visit to Yahoo Finance and Stock Analysis is recommended.

Why should I be interested in this post?

In essence, this article provides a perspective on market consensus based on financial analysts. For a student who would like to work in finance (either in the corporate world or the financial sector), it is important to know about the market consensus as it relates to both the corporate world and financial markets.

Related posts on the SimTrade blog

   ▶ Aamey MEHTA Market efficiency: the case study of Yes bank in India

   ▶ Louis DETALLE The importance of data in finance

   ▶ Louis DETALLE Bloomberg

Useful resources

Market consensus What is market consensus?

Faster Capital Navigating Markets: The Power of Market Analysis and Consensus Estimates

About the author

The article was written in March 2024 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).
Posted in Contributors | Leave a comment

Multiples valuation method for stocks

Multiples valuation method for stocks

Jorge Karam Dib

In this article, Jorge KARAM DIB (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2024-2025) introduces the method to evaluate stocks called “multiples valuation”.

How much should a stock be worth?

Valuing stocks is a complex yet essential endeavor for investors seeking to make informed decisions in the financial markets. Knowing if you are paying a fair price or if you are over or under paying for a stock is every investors question. Of course, a decision on whether investing or not in a company comes after a long due diligence of valuating the financials of the company, following their reports, and many more actions to ensure you are buying something of value. Some investors call this method “value investing”, when the investor value a stock above the actual price, it is said that the type of investing is “value”, trying to take advantage of the differential between the actual price and the theoretical price. And when they buy a stock for a competitive advantage that is not expected in the near future to concede, it is usually called “growth investing”. Although some famous investors disagree in these definitions, they are used frequently in the financial language.

While there is no one-size-fits-all approach to valuing stocks, investors often turn to a range of methodologies, one of which is multiples analysis. By examining multiples such as price-to-earnings (P/E), price-to-book (P/B), and price-to-sales (P/S), and many more, investors gain insights into how the market values a company relative to its earnings, assets, or revenue. In this article we will try to shine a light on this valuating method and walk through the benefits and limitations the method has.

Multiples valuation method

Multiples valuation method involves analyzing one or more multiples, such as the price-to-earnings (P/E), price-to-book (P/B), and price-to-sales (P/S) ratios, among others. Each multiple provides a unique perspective on how the market values a company relative to its earnings, assets, or revenue.

The price-to-earnings (P/E) ratio, for instance, compares a company’s stock price to its earnings per share (EPS), indicating how much investors are willing to pay for each dollar of earnings generated by the company. A low P/E ratio may suggest that the stock is undervalued, while a high P/E ratio could indicate overvaluation.

One key aspect of this method is that it is usually compared against the ratios of companies within the same industry. It is from the investor’s criteria to decide which filters to apply for deciding against what companies the objective should be compared with, but usually it should be on the same market, region can also be an important factor, and also the size.

There are many sources of information to consult the information from, many of them free. This platform simplifies the valuation by providing not only the information, but in some cases, the ability to connect through an API and do the consulting automatically through a query. In the next image is shown an example from Capital IQ, one of the most prestigious information sources in the financial world, about Walmart and some recommendations from the platform of similar companies in the market to facilitate the calculation.

Walmart’s comparison.
Walmart
Source: Capital IQ.

Calculations

Calculating multiples involves straightforward mathematical formulas that utilize key financial metrics derived from a company’s financial statements. If we use the case for P/E, then we would need to divide the “Market price per share” with the “Earnings per share”. After getting the ratio, let’s say of Walmart, the next step is to get the median P/E for the “similar” companies that the investor decided to compare the company with. With these two values the investor can start seeing a trend on where the company is positioned versus their competitors. The next step is to calculate the price per share of Walmart using the P/E of the similar companies, and see the comparison between the price with the original P/E versus the “mean” of similar companies.

Example: Walmart

This section will be dedicated to illustrate the method explained earlier using Walmart as an example and Capital IQ as the source of information. The first step is to consult the key financials as shown in the next picture.

Walmart’s key financials.
Walmart financials
Source: Capital IQ.

Next, compute the information with the comparable companies suggested by Capital IQ. Important to note that the companies can be added or withdrawn according to everyone’s own criteria.

Comparable analysis.
Comparable companies
Source: Capital IQ.

After retrieving all the information, the next step is to do the calculations explained earlier in the document. The mean EV/EBITDA ratio for the comparable companies and then recalculate the price of Walmart’s stock using the mean EV/EBITDA ratio.

Mean EV/EBITDA ratio.
EV/EBITDA ratio
Source: Capital IQ.

Valuation of Walmart’s stock.
Valuation
Source: Capital IQ.

In this case, we see an underappreciation of Walmart’s stock, this doesn’t mean that anyone shouldn’t buy stocks of the company, is just the perspective of the valuation method, and also it is not an investing advice.

Conclusions

The multiples valuation method provides investors with a valuable framework for assessing the worth of a stock by comparing it to similar companies within the same industry. By using this method, investors gain insights into how the market values a company relative to its earnings, assets, or revenue.

However, it’s important to recognize the limitations of this approach. Multiples analysis relies heavily on historical financial data and may not fully capture future growth prospects or qualitative factors such as industry dynamics and competitive positioning. Additionally, multiples are subject to fluctuations in market sentiment and may not always reflect the intrinsic value of a company accurately.

Despite these limitations, multiples analysis remains a widely used and valuable tool in the arsenal of investors. When applied judiciously and supplemented with thorough research and analysis, multiples can provide valuable insights into a company’s valuation and help investors identify potential investment opportunities.

Why should I be interested in this post?

This post is with the only intention for educational purposes. Targeting people who are interested in knowing more about valuation methods for stocks. In any way this article pretends to be an investment advice and/or suggestion. Any decision should be taken under personal responsibility and with their respective due diligence previous to the decision.

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Useful resources

McKinsey & Company The right role for multiples in valuation

Chastenet E. and A. Marion (2015) Valuation Using Industry Multiples: How to Choose the Most Relevant Multiples, Business Valuation Review, 34(4): 173-183.

Schueler A. (2020) Valuation with Multiples: A Conceptual Analysis, Journal of Business Valuation and Economic Loss Analysis, 15(1) pp. 20190020.

About the author

The article was written in March 2024 by Jorge KARAM DIB (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2024-2025).

Posted in Contributors, Financial techniques | Leave a comment

Explanations for the recent changes in the Mexican economic landscape

Explanations for the recent changes in the Mexican economic landscape

Jorge Karam Dib

In this article, Jorge KARAM DIB (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2024-2025) shares his thoughts about the different financial instruments recently available in Mexico that have been changing the economic landscape for the country and their residents in the recent years. He especially explains the role of high interest rates, new digital banks, and nonbanking financial instruments in Mexico’s recent booming economy, sharp Mexican peso appreciation, and strong increase in its GDP.

Interest rates in Mexico

For the last couple of years, the world has lived an era of high interest rates, mainly derived from the high inflation we got out of the pandemic and the war in Ukraine. Since then, the priority of most of the central banks of the world has been to cool down the economy and bring down inflation. Mexico has not been the exception. Mexico’s interest rates have been between 10% and 11% in the past three years. Some economists may consider this level -dangerously- high, but the country has seen mostly benefits like increasing peso’s appreciation, and a strong growth in the national GDP, from this level of interest rates than negative outcomes, and most important, Mexico’s government has been able to maintain the interest rates under a “controlled” level.

Evolution of Mexico’s interest rates.
Interest Rates Mexico
Source: Trading Economics.

The strategy of Mexico’s Central Bank has been very clear: to stay above the interest rates of the U.S.A. The benefits of staying above the interest of the USA’s is to target the remittances (money, mainly US Dollars, sent to Mexico, by migrant workers to their families), an objective that due the geographical conditions become very relevant. According to Statista, remittances represent a 4% of their GDP, either if it’s from migrant workers sending money to their families, or foreign investors trying to take advantage of the high interest rates in the country. “CETES” (Certificados de la Tesorerís de la Federación) is one of the most attractive instruments for foreign investments, because of the security CETES represent by being an instrument issued by the Mexican government, in the form of bonds mainly, with a return rate oscillating between 10%-12%.

CETES.
CETES
Source: S&P Dow Jones indices.

Digital Banks

There’s a recent uptrend in Latin America, but specially in Mexico of digital banks. In the last couple of years, we’ve seen multiple companies trying to gain market share, derived from the massive success of the Brazilian “unicorn” start-up Nu bank. In Mexico, the number of digital banks is starting to get closer to the traditional banks. Just in the last years, digital banks like Klar, Ualá, Hey Banco, RappiPay, among many others have entered the Mexican market with the objective to compete for market share with Nu bank.

Apart from the many benefits and functionalities that digital banks provide, better than the traditional banks, they’ve tried to attract more customers by trying to take advantage by offering the customers the possibility of investing their money inside their organization by adding a tool to their services called a “SOFIPO”, which will be explained further in the article. The return offered by each SOFIPO will depend on each institution issuing the instrument, but it will be mainly linked to the interest rate in the country. As we mentioned before, we are in a high interest rate season, which has turned into a “bidding war” for digital banks to offer better returns. As of February 2024, Nu bank offers one of the highest with 15%, Klar 14%, Hey Banco 11%, Ualá 15%.

The Mexican peso appreciated against the dollar in 2023 by 14%, reaching an eight-year low. Important to note that all these attractive financial instruments joined with a strong benefit from the world’s leading trends like nearshoring, have made Mexico become one of the best performing countries in terms of economy in the past few years and also one of the most attractive to invest in.

Mexican peso.
MXN
Source: Yahoo finance.

¿What is a SOFIPO?

Acronym for “Sociedad Financiera Popular” (Popular Financial Society), are defined as financial institutions -nonbanking- regulated by the CNBV (Comisión Nacional Bancaria y de Valores en México). They offer a wide variety of financial instruments such as personal loans, credits, financing for small companies, and more. The intention of why this instruments (SOFIPO’s) were created is mainly to open the financial services to a broader public and/or have more inclusion when it comes about investing, credits, and more.

Conclusions

There is no doubt that Mexico has a good advantage when it comes to macroeconomic trends, mainly due its geographical position. But recently, they have been able to complement the attractiveness with financial instruments and rates extremely attractive to the foreign audience and the local one. The challenge lies in keeping under control the high interest rates, even though inflation is not in double digits anymore, the benefits that the actual rates have brought to the country have been substantial, besides as the original plan is to follow with a margin the decisions of the U.S.A., there is no decision yet to bring down the rates. Not everything is positive with this financial conditions, the cost of debt in the country is very high at the moment, which will slow down the sales of houses and cars.

Why should I be interested in this post?

This post is with the intention to shine a light on potential advantages and trends that are happening in one of the most attractive countries, financially and economically speaking in the world. In any way this article pretends to be an investment advice and/or suggestion. Any decision should be taken under personal responsibility and with their respective due diligence previous to the decision.

Related posts on the SimTrade blog

   ▶ Cynthia LIN Financial products marketing in neobanks

Useful resources

Trading Economics Mexico interest rate

Mexico Business News Nonbanking financial institutions face historic opportunity

Statista Remesas en Mexico

S&P Dow Jones IndicesS&P BMV Government CETES Bond Index

El Economista Nu Mexico busca combatir el ahorro pasivo lanza oficialmente cuenta de ahorro

El Universal Guerra de tasas, Nu ofrece rendimientos de 15 en cuenta de ahorro

Mexico Business News Mexican peso appreciation 2023 affects public revenues

About the author

The article was written in March 2024 by Jorge KARAM DIB (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2024-2025).

Posted in Contributors, Financial news | Leave a comment